更便捷的畫決策分支圖的工具

Have you ever wondered:

您是否曾經想過：

• How did Google dominate 92.1% of the search engine market share?

  Google如何占領搜索引擎92.1％的市場份額？

• How did Facebook achieve 74.1% of social media market share?

  Facebook如何取得社交媒體市場份額的74.1％ ？

• How did Microsoft win over 77.7% of the Desktop OS market share?

  Microsoft如何贏得超過77.7％的桌面操作系統市場份額？

Aside from great vision, they all decided on how they do things, leading them to their triumph. Google decided to focus its search engine to provide better user experience, instead of monetization. Learning from the early adopters, Facebook decided to plan its growth, time its entry, and manage its public relation wisely. Microsoft decided to build Windows with compatibility in mind, reducing future issues so they can innovate even more.

除了有遠見，他們都決定如何做事，帶領他們走向勝利。 Google決定將重點放在搜索引擎上，以提供更好的用戶體驗，而不是通過獲利 。 向早期采用者學習，Facebook決定計劃其發展，安排其進入時間并明智地管理其公共關系 。 微軟決定在構建Windows時考慮到兼容性 ，以減少將來出現的問題，以便他們可以進行更多創新。

They all made great decisions, bet on it — and won.

他們都做出了偉大的決定，下了賭注，并且贏了。

As one who’s in the data science field, being data-driven is a must. Deciding our actions based on data is a normal thing to do. It’s in the job description after all. Yet, my mentor once said, “be more than a data scientist”. I figured out what it means later on. Not all problems can be solved using data. Maybe it can, but is it the best approach?

作為數據科學領域的一員，必須以數據驅動。 根據數據確定我們的行動是正常的事情。 畢竟它在職位描述中。 但是，我的導師曾經說過，“不僅僅是一名數據科學家”。 后來我弄清楚了這是什么意思。 使用數據并不能解決所有問題。 也許可以，但這是最好的方法嗎？

Other than data science and analytics, 2 more essentials could help us form better decisions. Finding the balance of all three is important since our decisions defines our future. Whether we want to solve personal matters, build a product, or start a business — we have to decide our next step.

除了數據科學和分析之外，還有2項基本要素可以幫助我們制定更好的決策。 找到三者之間的平衡很重要，因為我們的決定決定了我們的未來。 無論是要解決個人事務，生產產品還是開展業務，我們都必須決定下一步。

Take a look at this graph. Imagine you have built a startup. These bars represent your monthly product sales.

看一下這個圖。 假設您已經建立了一家初創公司。 這些條形代表您的每月產品銷售量。

The first 8 bars show stable growth, which is good.

前8個小節顯示穩定增長，這很好。

You experiment and manage to growth hack it by 3 times next month.

您可以進行實驗并設法在下個月將其黑客入侵3次。

You’re happy, but have no absolute idea of what has happened.

您很高興，但是對發生的事情一無所知。

A screenshot from my Medium Stats is perfect to demonstrate the 3 essentials. Image by Author.我的中型統計數據的屏幕截圖非常適合演示這三個要素。 圖片由作者提供。

Keep this graph in mind as you read through.

閱讀時請牢記此圖。

分析工具 (Analytics)

According to Cambridge, analytics is a process in which a computer examines information using mathematical methods in order to find useful patterns.

根據Cambridge的說法，分析是計算機使用數學方法檢查信息以找到有用的模式的過程。

Data is the new oil. Analytics help us achieve better business performance through insights from data. The demand for analytics is growing, giving rise to data scientists that became the sexiest job of the 21st century. Nowadays, most organizations have applied descriptive, prescriptive, and predictive analytics to unlock their full potentials.

數據是新的石油。 通過數據洞察，分析可幫助我們提高業務績效。 對分析的需求不斷增長，這催生了成為21世紀最性感的工作的數據科學家 。 如今，大多數組織已應用描述性，描述性和預測性分析來釋放其全部潛力。

I work in analytics myself. Most of my output is used to decide strategic moves and discover answers to business problems. Furthermore, it could transform new opportunities into realities. Without data, it’s like wandering with no direction.

我自己從事分析工作。 我的大部分輸出都用于決定戰略舉措和發現業務問題的答案。 此外，它可以將新機會轉化為現實。 沒有數據，就像無方向徘徊。

Google even got a Chief Decision Scientist; ensuring the use of data and analytics to fuel the decisions on their products — or they called it decision intelligence. They invest in it in exchange for better business decisions.

谷歌甚至有首席決策科學家 ; 確保使用數據和分析來推動其產品上的決策，或者他們稱之為決策智能 。 他們在其中投資以換取更好的業務決策。

The beauty data is — it’s based on fact. We can only find the truth with data.

美容數據是-它基于事實。 我們只能用數據找到真相。

• Is your new business working well?
  您的新業務運作良好嗎？
• Can we reduce the cost?
  我們可以降低成本嗎？
• Which strategy is more efficient to put in place?
  哪種策略更有效？
• How is the future trend?
  未來趨勢如何？

Analytics can answer all these questions.

Analytics(分析)可以回答所有這些問題。

Say you have used quantitative data to optimize processes and fuel your business strategy. Your startup is growing at a constant rate until the 8th month. But, is that it? Don’t you want to raise the ceiling and go beyond? What else can you do?

假設您已使用定量數據來優化流程并推動您的業務戰略。 直到第8個月，您的創業公司都將以恒定的速度增長。 但是，是嗎？ 您是否不想提高天花板并超越？ 你還能做什么？

直覺 (Intuition)

According to Cambridge, intuition is an ability to understand or know something immediately based on your feelings rather than facts.

劍橋大學認為 ，直覺是一種根據您的感受而不是事實立即理解或了解某些東西的能力。

How many times did you believe in your hunch and succeed? Probably a few times. Intuition just pops up in your mind before you know it. When done right, that instant idea may lead you to create major impacts.

您相信自己多少次成功了？ 大概幾次。 直覺就突然出現在您的腦海中。 如果做得對，那立即的想法可能會導致您產生重大影響 。

People dreamt of going to space but very few are serious to think of how to get there. Elon Musk decided to believe his gut along with his vision. He then built an innovation, something that hasn’t existed yet. Now, he has proved that “SpaceX can do what it says it wants to do”.

人們夢想著要去太空，但是很少有人認真思考如何到達太空。 伊隆·馬斯克(Elon Musk)決定相信自己的直覺和他的遠見。 然后，他進行了一項創新，這還不存在。 現在，他證明了“ SpaceX可以做到其想做的事情 ”。

However, an intuition like his is one-of-a-kind. What about the rest of us? We can’t quantify the value of someone’s intuition but the good news is: every person can strengthen his/her intuition by using it over time.

但是，像他這樣的直覺是獨一無二的。 那我們其余的人呢？ 我們無法量化某人的直覺的價值，但好消息是：每個人都可以通過逐漸使用它來增強自己的直覺。

Still, it’s best practice to believe intuition when it’s validated by logic, reasoning, and data. I did trust my blind intuition at work once in a while and most of the time, it didn’t work well. Ideas build by feelings alone will more likely to fail. Relying on intuition alone can’t get you very far. After all, every journey is a marathon, not a sprint.

不過，最好的做法是在通過邏輯，推理和數據驗證直覺時相信直覺。 我確實偶爾會相信我的盲目直覺，在大多數情況下，這種感覺并不奏效。 僅憑感覺建立的想法更有可能失敗。 僅僅依靠直覺不會使您走得太遠。 畢竟，每一次旅程都是一場馬拉松，而不是短跑。

In the 9th month, you believe your intuition and implement a weird strategy. Your sales grew 3 times the next month. You’re happy. It’s unexpected. Although the real why remains a question.

在第9個月中，您相信自己的直覺并執行怪異的策略。 您的銷售在下個月增長了3倍。 你很高興。 真是出乎意料 雖然真正的原因仍然是一個問題。

研究 (Research)

According to Cambridge, research is a detailed study of a subject, especially in order to discover (new) information or reach a (new) understanding.

劍橋大學認為 ，研究是對一個主題的詳細研究，特別是為了發現(新)信息或達成(新)理解。

Analytics are quantitative. Intuition is more or less a mystery. Research fills in the gap with its qualitative study. With it, we can gain a deeper understanding beyond feelings and numbers.

分析是定量的。 直覺或多或少是個謎。 研究填補了其定性研究的空白。 有了它，我們不僅可以獲得感覺和數字，還可以獲得更深刻的理解。

Apple took 1st place while Samsung took 6th place in the Best Global Brands 2019 by Interbrand. As a mobile phone vendor, they’re leading the industry with 30.9% and 24.8% market share worldwide. But that aside, let’s take a look at China’s Apple.

在Interbrand的2019年度最佳全球品牌中，蘋果名列第一，三星名列第六。 作為手機供應商，他們以30.9％和24.8％的全球市場份額引領行業。 除此之外，讓我們看看中國的蘋果 。

Unlike those top 2 who innovate as well as set the bar for its users, Xiaomi approaches it the other way around. Lei Jun built an ecosystem where “fans” co-design and evangelize their products. Lei diligently took into account all the researches together with feedbacks, then — took the 1st place of market share in India, blowing Samsung away.

與那些創新并為用戶設定標準的前2名小米不同，小米采用了相反的方法。 雷軍建立了一個生態系統， “粉絲”可以共同設計和宣傳他們的產品 。 Lei勤奮地考慮了所有研究和反饋，然后–占據了印度市場份額的第一位 ，將三星趕走了。

We can use logic on numbers but empathy on feedbacks. Research can answer problems by understanding people. It goes well with one habit from 7 Habits of Highly Effective People — “seek first to understand, then to be understood”.

我們可以對數字使用邏輯，而對反饋使用同理心。 研究可以通過了解人們來回答問題。 它與7個高效人的習慣中的一個習慣相得益彰 -“首先尋求理解，然后理解”。

I keep this habit in mind when faced with problems that include several people. Understanding their point of view — think — then offer a solution. The result: we decided on a solution faster, without needless arguments. If you’re a data science enthusiast, consider reading more about other habits here.

當遇到包括幾個人的問題時，我謹記這個習慣。 了解他們的觀點(思考)，然后提供解決方案。 結果：我們更快地決定了解決方案，而沒有多余的爭論。 如果您是數據科學愛好者，請考慮在此處閱讀有關其他習慣的更多信息。

No matter how good your analytics & intuitions, people are always involved. Listen to their voice.

無論您的分析和直覺多么出色， 總會涉及到人們 。 聽他們的聲音。

Be aware though, too much research without good sense and data may lead to a false decision. One common mistake is poor research sampling: listening too much on the minority while overlooking the majority.

但是請注意，太多的研究缺乏良好的理智和數據，可能會導致錯誤的決定。 一個普遍的錯誤是研究抽樣不力：在聽少數派意見的同時卻忽略了大多數意見。

At the start of the 10th month, you connect and chat with your customers. Not two but many. Now that you understand the reason behind your sudden growth — you strike a new record with ease in the following month.

在第10個月初，您可以與客戶建立聯系并聊天。 不是兩個，而是很多。 現在，您了解了突然增長的原因-您將在下個月輕松創下新紀錄。

Congratulations! ?

恭喜你！ ?

尋找平衡 (Finding the Balance)

We make decisions every day. Some good, some bad. Take the bad ones as our learning curve and strive for better decisions every day. We are who we decide to be.

我們每天都會做出決定。 有些好，有些壞。 將壞問題作為我們的學習曲線，每天努力做出更好的決定。 我們是我們決定成為的人。

“I am not a product of my circumstances, I am a product of my decisions.” — Stephen R. Covey

“我不是我所處環境的產物，而是我所做出決定的產物。” —斯蒂芬·R·科維

To sum it up, these three essentials interconnect and empower each other:

綜上所述，這三個要點相互聯系并相互賦能：

1 Analytics will support and validate your intuition & research. It helps you to better sustain your venture and reach its greatest potential. Even so, clinging too much on it will get you nowhere.

1 Analytics(分析)將支持和驗證您的直覺和研究。 它可以幫助您更好地維持自己的事業并發揮最大的潛力。 即使這樣，過分堅持下去也無濟于事。

2 Intuition can yield massive impact and act as a guide to extract valuable insights from your analytics & research. Believe in your hunches while backing it up with your experience. Wrong hunches may lead to failure.

2直覺可以產生巨大的影響，并可以作為指導，從您的分析和研究中提取有價值的見解。 相信自己的預感，同時根據自己的經驗進行備份。 錯誤的預感可能會導致失敗。

3 Research enriches intuition & analytics by understanding the problem. Using qualitative insights, you can replicate your decision in more ways than one. Be sure to hear from all kinds of people though.

3研究通過了解問題來豐富直覺和分析。 利用定性見解，您可以通過多種方式復制決策。 但是一定要聽取各種各樣的人的意見。

Remember: big decision carries a big risk. Balance all these 3 essentials to mitigate it and find your next best action.

請記住：重大決策會帶來巨大風險。 平衡所有這三個要素，以減輕壓力并找到下一個最佳動作。

This post was inspired by “#FirstPrinciples Ep06 with Ravi Mehta”. Thank you for sharing! 🙌

這篇文章的靈感來自“ Ravi Mehta的 #FirstPrinciples Ep06 ”。 感謝你的分享！ 🙌

All market share data are the last 1 year from July 2020, sourced from Statcounter Global Stats.

所有市場份額數據均來自 Statcounter Global Stats ，是2020年7月以來的最近1年 。

翻譯自: https://towardsdatascience.com/3-essentials-to-make-better-decisions-9b2cdc60365e

更便捷的畫決策分支圖的工具

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