Google’s high-minded hiring methods are simply too dazzling for ordinary companies
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Prologue | Its correctness is simply too dazzling for us
“Riddle-style interview questions are meaningless, so abolish them.”
“Academic background does not correlate with post-hire performance, so discard it.”
Google’s hiring reforms, as described in the original article, are strikingly clear-cut. They verify ideas with data, discard traditions if no correlation is found, and concentrate resources only where impact exists. It is close to an ideal model of treating HR as a science.
But Google operates with around three million applicants a year, hires tens of thousands, and possesses data on nearly 200,000 employees. It has dedicated analytics teams and enough slack to survive repeated failures without shaking the organization. In other words, it practices HR from an extraordinarily elevated vantage point.
What about ordinary companies, especially small and mid-sized ones?
Applicant pools are limited. HR teams are small. Neither time nor budget can be devoted exclusively to hiring. The margin for experimentation is thin.
That is why what is needed is not Google’s “rationality of discarding,” but a rationality of fully using what is at hand. Before eliminating signals, they must be exhausted. Hiring needs to be rebuilt from that premise.
Chapter 1 | Hiring Is Not a Search for the ‘Correct Answer’
The most dangerous thing in hiring is the conviction that “this person will definitely work out.” People are multi-dimensional and change with context. Some grow under a different manager; others, despite being highly capable, collapse due to cultural mismatch.
An interview lasts only a few hours, a résumé only a few pages. Expecting to identify a “correct answer” from such fragments is itself a flawed assumption.
Hiring is not about finding the right answer.
It is about improving matching accuracy under severe information constraints.
Seen this way, binary debates—whether academic background is right or interviews are万能, whether riddles are good or bad—lose meaning. None is universal; all have some value. Hiring is the craft of layering weak signals to create a structure that fails less often.
Chapter 2 | Academic Background Is Neither ‘Useless’ Nor ‘Absolute’—But It Is Material
Claims like “you can’t judge people by education” or “many succeed without degrees” are true, but they miss the premise of hiring. Hiring deals not with exceptions, but with distributions and probabilities.
In sports, there are prodigies who start late and still reach the top. Yet in aggregate, those who began early show more stable outcomes. Education works the same way.
Academic credentials are neither proof of ability nor guarantees of character. But they tend to have smaller variance in areas such as learning persistence, tolerance for difficulty, and adaptation to selection systems. Especially for early-career hires, they can function as proxies for:
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basic learning capacity,
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sustained effort,
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experience in competitive evaluation environments.
The key point is that education is not proof of excellence, only a signal of relatively higher probability. “Hiring because they went to Tokyo University” is foolish—but declaring education irrelevant is equally simplistic.
Chapter 3 | What Do Riddle Questions and Verbal Agility Actually Measure?
Critics often say riddle questions are meaningless because there is no right answer. That misses the point. What they measure is situational processing ability:
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grasping incomplete situations,
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forming plausible hypotheses,
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improvised verbalization,
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resistance to cognitive breakdown.
In roles requiring quick judgment, negotiation, or improvisation, such responsiveness is an asset. The problem is not riddles themselves, but how they are used. As comedian Kamigata Ryūtarō’s famous anecdote suggests, value is determined by priority. If interviewers do not understand what they are measuring, evaluation devolves into liking “fun” or “loud” candidates.
Chapter 4 | The Risks of Skills and Achievements as the ‘Largest Piece’
Skills and track records are the strongest indicators—highly reproducible and easy to justify. Yet even they are context-dependent. Success in a large corporate structure may not translate to a small firm. The “instant contributor myth” often damages teams.
Because it is the largest piece, it must not be overtrusted. Strong signals require the most careful scrutiny.
Chapter 5 | There Is No ‘Perfect Solution’ for SME Hiring
SMEs cannot devote all resources to hiring. Applicant numbers are small, budgets are tight, and HR staff are limited. Hiring is not about choosing the best of a hundred, but deciding whether a candidate is viable or not.
What is needed is not the rationality of exclusion, but the rationality of selection:
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use education as a proxy,
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conversations to assess collaboration risk,
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riddles for responsiveness,
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achievements as the largest piece.
Use everything, but treat nothing as decisive.
Chapter 6 | The Essence of HR Is Shaving Off the Edges
Betting everything on a single indicator—education, eloquence, experience, or “good vibe”—is faith, not hiring. HR’s role is to lay out all usable data, view them holistically, and shave off extremes. Strong fits may justify ignoring some doubts—but only after examining them.
Epilogue | HR Is the Craft of Optimizing Combinations
Organizations are collectives. Hiring, evaluation, and placement all follow the same principle: combining diverse pieces to maximize overall effect.
Google’s hiring is right. But so is our reality. If global giants gain precision by discarding signals, ordinary companies must raise their batting average by exhausting them. There is no need to imitate a dazzling ideal. The practical solution is to improve hiring accuracy within limited resources.
Read in Japanese ↓（For Japanese learners!）↓
グーグル視点の採用と、一般企業視点の採用を同一視はできない（2026.2.10）
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