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Review Buku: Superforcasting - Phillip E. Tetlock, Dan Gardner

Buku ini cuma 309 halaman, tapi saya ngabisininya dalam waktu 12 hari, artinya speed baca saya ±23 halaman per hari. speed  terendah di tahun 2021.

Kesibukan saya naik jadi 2x lipat setelah ikutan ngurusin jadi tim inti

ok balik ke judul.

Buku ini saya baca melalui Google Play Books.

buku Superforecasting
buku Superforecasting

Secara umum bahasanya ga terlalu susah dimengerti. Awalnya saya mengira bakal banyak ngebahas soal forecasting secara teknikal dan angka angka.. ternyata tidak.

Jadi buku ini lebih ke cerita sih, cerita tentang metodologi forecasting super, cerita tentang melakukan forecasting yang super, cerita tentang apa di balik superforecasting, cerita tentang subjek orang di balik superforcasting.

Yang intinya, forecasting yang super akurat (superforecating), dihasilkan dari orang orang terbaik yang sudah disaring bertahun tahun. Dalam tahun tahun seleksi itu, si penulis (PIC project ini), ngasih pertanyaan pertanyaan forecast / ramalan ke seluruh peserta. Per tahun bisa 100 pertanyaan.

Dari sekian banyak pertanyaan itu, dan dari 2-3 tahun project berlangsung, akan ketahuan mana saja orang yang berhasil memberikan ramalan terbaik, dengan metode scoring tertentu.

khawatir ini hanya "luck" saja, orang orang terpilih itu ditanding-kan lagi hasil hasil forecastnya dengan orang acak. Dan hasilnya tetep para superforecaster itu menang.

Keren kan ya? jadi fakta bahwa memang ada orang2 yang "jago" dalam meramal, tapi jangan salah artikan dengan peramal mistis loh ya.. Para superforcaster ini pasti pernah salah juga kok, cuman tingkat benarnya lebih sering daripada orang pada umumnya. Dan para forecaster ini umumnya tidak bisa meramalkan kepastian, tapi dengan presentase.. contoh: ya besok 80% hujan --> jadi lebih ke peluang besok hujan 80%, bukan YA BESOK PASTI HUJAN

Buku ini ngemention berkali kali soal buku Thinking Fast and Slow dari Daniel Kahneman, dan juga ngemention buku Black Swan dari Black Swan. Bahkan untuk yang Black Swan, ada sub-bab tersendiri. Untungnya saya udah pernah baca buku tersebut, udah saya review juga di blog ini, sehingga dalam membaca buku ini saya tidak terlalu "gap", cukup bisa ngikutin arahan bahasannya.

baca review saya tentang 2 buku lainnya:
secara umum saya merekomendasikan buku ini, buat siapa saja. Hasil yang paling terasa buat saya adalah, saya jadi optimis, bahwa semua yang bisa terukur, itu bisa diprediksi. Baik terukur kualitatif, maupun kuantitatif. Prediksi pun tergantung seberapa tinggi errornya, error tinggi, prediksi mudah, error kecil, prediksi makin sulit.

Ini beberapa catatan saya tentang buku ini:

  • Meteorologists know that better than anyone. They make large numbers of forecasts and routinely check their accuracy—which is why we know that one- and two-day forecasts are typically quite accurate while eight-day forecasts are not.
  • The point is now indisputable: when you have a well-validated statistical algorithm, use it .
  • Experiments are what people do when they aren’t sure what the truth is.
  • “estimating is what you do when you do not know.”
  • To do that, we have to interpret the meaning of the Brier scores, which requires two more things: benchmarks and comparability.
  • So why did one group do better than the other? It wasn’t whether they had PhDs or access to classified information. Nor was it what they thought —whether they were liberals or conservatives, optimists or pessimists. The critical factor was how they thought
  • . But as Mauboussin noted, there is an elegant rule of thumb that applies to athletes and CEOs, stock analysts and superforecasters. It involves “regression to the mean.”
  • Statisticians call that the base rate—how common something is within a broader class. Daniel Kahneman has a much more evocative visual term for it. He calls it the “outside view”—in contrast to the “inside view,” which is the specifics of the particular case.
  • When we make estimates, we tend to start with some number and adjust. The number we start with is called the anchor. ..... And a better anchor is a distinct advantage.
  • Hypotheses like these are the ideal framework for investigating the inside view.
  • People should take into consideration evidence that goes against their beliefs . It is more useful to pay attention to those who disagree with you than to pay attention to those who agree .
  • you can’t outguess the seasonal averages.
  • Distinguish as sharply as you can between the known and unknown and leave no assumptions unscrutinized.
  • if you spot potentially insightful new evidence, you should not hesitate to turn the ship’s wheel hard.
  • So there are two dangers a forecaster faces after making the initial call. One is not giving enough weight to new information. That’s underreaction. The other danger is overreacting to new information, seeing it as more meaningful than it is, and adjusting a forecast too radically.
  • “I feel like I should be doing better than most [on military questions]. So if I realize that I’m wrong, I might spend a few days in denial about it before I critique myself.”
  • Many studies have found that those who trade more frequently get worse returns than those who lean toward old-fashioned buy-and-hold strategies.
  • “I update constantly,”
  • People with the fixed mindset say things like “I’m bad at math”... Fixed-mindset kids gave up. Growth-mindset kids knuckled down.
  • Try, fail, analyze, adjust,
  • The knowledge required to ride a bicycle can’t be fully captured in words and conveyed to others. We need “tacit knowledge,”
  • But not all practice improves skill. It needs to be informed practice. You need to know which mistakes to look out for—and which best practices really are best.
  • To learn from failure, we must know when we fail.
  • This is a familiar paradox: success can lead to acclaim that can undermine the habits of mind that produced the success. Such hubris often afflicts highly accomplished individuals. In business circles, it is called CEO disease.
  • No one ever described Winston Churchill, Steve Jobs, or any other great leader as “humble.” Well, maybe Gandhi. But try to name a second and a third.
  • “Great success requires boldness and daring, but good judgment must take precedence,”
  • When Walmart found it was building stores faster than it could develop store managers, it created a “leadership academy” to get prospects ready for promotion sooner.

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