天雨傘預測行動法The Sky · Rain · Umbrella Method
看見天色、預判下雨、先把傘撐好。這個月我們練一件事：把「觀察」變成「判斷」，再變成「行動」，讓主管從救火，走到防火。
Read the sky, predict the rain, open the umbrella in time. This month we practise turning observations into judgement, and judgement into action — moving from firefighting to fire prevention.
1天雨傘是什麼？What is Sky · Rain · Umbrella?
一句話：先看事實，再做判斷，最後決定行動。三步都要有，順序不能跳。
In one line: facts first, then judgement, then action. All three steps, in that order.
我們每天都在用天雨傘，只是到了工作上，常常只做了一半。
We all do this every day. At work, we often stop halfway.
天 看見事實See the facts
現在發生了什麼？有哪些數據或現場觀察？
What is happening? Which numbers or observations do we have?
雨 解讀預測Read & predict
這代表什麼？接下來可能會怎樣？對目標影響多大？
So what? What is likely to happen next, and how much does it affect our goal?
傘 決定行動Decide the action
所以我們要做什麼？誰負責、何時完成、做到什麼程度？
So what do we do? Who owns it, by when, and to what standard?
從顧問業的基本功而來A consultant’s basic drill
天雨傘來自顧問業訓練新人的問題解決方法，常被歸於麥肯錫等顧問公司，在日本商業書中以「空・雨・傘」廣為流傳。它對應的是 事實 → 洞察 → 行動（Fact → Insight → Action）這條思考鏈。
The method comes from problem-solving training in consulting firms (often credited to McKinsey) and became widely known in Japanese business books as “Sora · Ame · Kasa”. It mirrors the chain Fact → Insight → Action.
還記得八月 MECE 課最後那張補充嗎？訊息分三種：記述性（天空烏雲密佈）、評價性（降雨機率超過 80%）、決策性（帶把傘比較穩當）。天雨傘就是把這三種訊息排好隊。
Remember the extra slide in August’s MECE lesson? Messages come in three kinds: descriptive (dark clouds), evaluative (80% chance of rain) and decisional (take an umbrella). This method lines them up in order.
讓預測更穩Make predictions sturdier
- 雨，寫兩種：「最可能發生的」和「最需要防範的」。
- Two kinds of rain: the most likely, and the one to guard against.
- 傘，分兩層：預防傘（現在就做）＋應變傘（雨真的下了才啟動）。
- Two layers of umbrella: prevention (act now) + contingency (trigger only if it rains).
- 設一個晴雨表：一個預警指標＋檢視時間，天氣變了就換傘。
- Set a barometer: one warning indicator + a review date. Change umbrellas when the weather changes.
為什麼值得練？Why it is worth practising
報告更聚焦Sharper reports
8 分鐘簡報講完天、雨、傘，聽的人馬上能決策。
An 8-minute report that covers sky, rain and umbrella lets leaders decide on the spot.
從救火到防火From firefighting to prevention
比別人早一步看到雨，就不必淋濕再處理。
Spot the rain early and you will not be fixing things soaked.
共識更快Faster alignment
先對齊事實，再討論判斷，會議少一半爭論。
Agree on facts first, then debate judgement. Half the arguments disappear.
行動可追蹤Trackable action
每把傘都有人、有時間、有指標，下個月可以回頭檢視。
Every umbrella has an owner, a date and a measure, so next month we can review it.
怎麼開始？五個步驟How to start: five steps
- 定題目：Name the issue: 我要預測的是哪一件事？（例如：春節住房、聖誕檔期人力）what exactly are we predicting? (e.g. Lunar New Year occupancy)
- 收集天：Gather the sky: 2–3 個數據或現場觀察，越具體越好。2–3 numbers or observations, as concrete as possible.
- 推估雨：Predict the rain: 至少兩種情境，標出可能性與影響。at least two scenarios with likelihood and impact.
- 撐好傘：Open the umbrella: 1–3 個行動，寫清楚誰、何時、做什麼。1–3 actions: who, when, what.
- 掛晴雨表：Hang a barometer: 設預警指標與檢視時間，持續追蹤。a warning indicator and a review date.
跟前三個月接起來Connecting the last three months
紅色能量「形成共識、做出決策」，就是在撐傘。
Red energy — reach consensus and decide — is opening the umbrella.
讓「天」的事實分得清楚、不重疊、不遺漏。
Keeps your “sky” facts clean: no overlaps, no gaps.
SWOT 的機會與威脅，常常就是你的「天」；天雨傘幫你推到行動。
SWOT’s opportunities and threats are often your “sky”; this method pushes them into action.
漫步的應用場景Where Meander can use it
2三個漫步情境範例Three Meander-style cases
同一套三步驟，放進營運、帶人、策略三種場景。點上方分頁切換。
One method, three arenas: operations, people leadership and strategy. Use the tabs to switch.
☁️ 天｜事實Sky · Facts
- 訂房網站上，演唱會當週的搜尋量比上月同期高約 40%
- 週六目前預訂 72%；去年同類活動最後到 98%
- 週六房務班表已排滿，另有 2 位已請假
- Search volume for that week is ~40% above the same period last month
- Saturday is 72% booked; a similar event last year ended at 98%
- Saturday housekeeping roster is full and 2 staff are on leave
🌧 雨｜預測Rain · Prediction
- 最可能：週六滿房，入住集中在 15:00–17:00，週日中午退房擠在一起
- 要防範：房務量能不足 → 清房延遲、客人等房、負評上升
- 另一種天氣：活動延期，需求回落
- Most likely: full house; check-ins pile up 15:00–17:00, check-outs cluster Sunday noon
- Guard against: housekeeping short → late room turnover, waiting guests, bad reviews
- Other weather: the concert is postponed and demand drops
☂️ 傘｜行動Umbrella · Actions
- 營收：週六房價分段調升、推兩晚方案（營收負責人，本週三前）
- 人力：跨館支援 2 位房務；櫃台尖峰加開一個報到窗口（前廳主管）
- 體驗：訂房後發送線上預辦入住與行李寄存提醒（訂房組）
- Revenue: tiered Saturday rates and a two-night package (revenue lead, by Wed)
- People: borrow 2 housekeepers from a sister hotel; open an extra check-in counter at peak (front office)
- Experience: send online pre-check-in and luggage-storage reminders (reservations)
📈 晴雨表Barometer
- 每天早上看週六預訂率
- 週四若低於 85%，釋出部分房間做限時促銷
- 週一檢視：清房時間、評論分數
- Check Saturday occupancy every morning
- Below 85% by Thursday → release rooms for a flash promotion
- Monday review: turnover time and review scores
☁️ 天｜事實Sky · Facts
- 近一個月外場新人 3 位，2 位在試用期內提離職
- 離職談話都提到「尖峰時段沒人教，只被催」
- 同期「上菜慢」的客訴從每月 2 則變 6 則；聖誕檔訂位已達七成
- 2 of 3 new floor staff resigned during probation this month
- Exit talks both said “no one teaches us at peak, we just get rushed”
- “Slow service” complaints rose from 2 to 6 a month; Christmas bookings already 70% full
🌧 雨｜預測Rain · Prediction
- 最可能：檔期人手不足，資深同仁加班變多、服務節奏亂
- 要防範：資深同仁也累倒，出現第二波離職
- 影響：聖誕檔期營收與評論分數同時受傷
- Most likely: short-handed in peak season; seniors do overtime, service rhythm breaks
- Guard against: seniors burn out and a second wave of resignations follows
- Impact: both festive revenue and ratings take a hit
☂️ 傘｜行動Umbrella · Actions
- 帶人：「尖峰夥伴制」，新人前兩週跟一位資深學長姊，不單獨顧區（外場主管，下週起）
- 溝通：每日開店前 10 分鐘簡報：今日訂位、主推菜、分工
- 留才：試用期第 7 天、第 30 天各一次一對一回饋
- Coaching: a “peak buddy” system — new staff shadow a senior for two weeks, never alone on a section (floor manager, from next week)
- Briefing: a 10-minute pre-shift huddle: bookings, signature dishes, roles
- Retention: one-to-one feedback on day 7 and day 30 of probation
📈 晴雨表Barometer
- 新人 30 天留任率
- 平均出餐時間、「上菜慢」客訴則數
- 每週例會看一次，連兩週變差就啟動支援班
- 30-day retention of new hires
- Average serving time and “slow service” complaints
- Review weekly; two bad weeks in a row → call in support shifts
☁️ 天｜事實Sky · Facts
- 進口牛肉與乳製品報價，三個月上漲約 12%
- 餐飲部門食材成本率從 32% 升到 35%
- 同商圈兩家競品已調漲套餐價格
- Imported beef and dairy quotes up ~12% in three months
- F&B food-cost ratio rose from 32% to 35%
- Two nearby competitors have raised set-menu prices
🌧 雨｜預測Rain · Prediction
- 最可能：趨勢延續，上半年毛利率再降約 3 個百分點
- 要防範：全面漲價影響回客率與評論
- 另一種天氣：供應恢復、價格回落，鎖價反而吃虧
- Most likely: the trend continues; gross margin drops ~3 points in H1
- Guard against: across-the-board price rises hurt repeat visits and reviews
- Other weather: supply recovers and locked-in prices become a loss
☂️ 傘｜行動Umbrella · Actions
- 採購：與兩家供應商談半年分批鎖價，加入在地替代品項（採購，11 月底）
- 菜單工程：找出「高成本、低銷量」品項替換，主推高毛利季節套餐（主廚＋營運）
- 定價：不全面漲價，先在兩家店測試小幅調整
- Purchasing: partial six-month price locks with two suppliers, add local substitutes (purchasing, end of Nov)
- Menu engineering: replace high-cost low-sellers, push high-margin seasonal sets (chefs + ops)
- Pricing: no blanket increase; test small adjustments in two outlets first
📈 晴雨表Barometer
- 每月食材成本率
- 超過 34% 啟動第二階段（擴大調價店數）
- 測試店的來客數與客單價，月會檢視
- Monthly food-cost ratio
- Above 34% → phase two (more outlets adjust prices)
- Covers and average spend at test outlets, reviewed monthly
3提問時間Q&A
先看看大家最常問的四題；還有疑問，直接寫在提問板，我現場回答。
Start with the four most common questions. Anything else, post it on the board and I will answer live.
天雨傘跟 SWOT 有什麼不同？How is this different from SWOT?
SWOT 幫你盤點全局；天雨傘針對「一個變化」做判斷與行動。SWOT 裡的機會與威脅，常常就是天雨傘的「天」。
SWOT maps the whole picture; this method responds to one specific change. SWOT’s opportunities and threats are often your sky.
「雨」預測錯了怎麼辦？What if my rain prediction is wrong?
雨本來就是假設。寫兩種情境、掛好晴雨表，天氣變了就換傘。重點是比別人早想，不是一定猜中。
Rain is a hypothesis. Write two scenarios, set a barometer and switch umbrellas when the weather changes. The point is thinking early, not guessing right.
手上數據不夠，還能寫「天」嗎？Not enough data — can I still write the sky?
可以用現場觀察，但要具體：誰、何時、發生幾次。「客人好像變少」→「這週平日午餐 142 人，上週 171 人」。
Yes, use observations, but make them concrete: who, when, how often. “Fewer guests” → “142 weekday lunch covers vs 171 last week”.
傘要寫幾把？How many umbrellas?
1–3 把就好。挑影響最大、你能掌控的；每把都寫清楚誰、何時、做什麼。
One to three. Pick those with the biggest impact that you control, each with who, when and what.
🙋 提問板Question board
4隨堂測驗：五題單選Quick quiz: five questions
選完按「交卷」，馬上看到哪幾題錯、正確答案與解說。可以重做，答案只存在你自己的裝置。
Press “Submit” to see which ones you missed, the right answers and why. You can retry; answers stay on your device.
5動手演練：選你的單位Practice: pick your unit
選好單位，讀題目，直接在下方填寫；手寫的也可以拍照上傳。送出後會出現在第 6 段的答案牆。
Choose your unit, read the brief and write below — or upload a photo of your handwritten notes. Your answer appears on the wall in step 6.
👆 先選一個單位，題目會出現在這裡。👆 Pick a unit first; your brief will appear here.
🏨 旅館題：2027 春節連假營運預備Hotel: Lunar New Year 2027 readiness
春節連假是全年最重要的檔期之一。請以你所在的旅館為對象，用天雨傘寫一份「春節營運預備」摘要。可以想想：訂房進度、去年同期、房務與櫃台人力、競業動態、客人組成。
Lunar New Year is one of the most important periods of the year. For your hotel, write a readiness summary with the method. Think about booking pace, last year, housekeeping and front-desk staffing, competitors and guest mix.
🍽️ 餐廳題：聖誕跨年檔期預備Restaurant: Christmas & New Year’s Eve readiness
聖誕到跨年是業績高峰，也最容易出狀況。請為你的餐廳（或你負責的區域）寫一份檔期預備摘要。可以想想：訂位與包場、食材與備料、內外場排班、出餐節奏、客訴與評論。
Christmas to New Year is peak season — and peak risk. For your restaurant (or your section), write a readiness summary. Think about bookings and private events, ingredients and prep, kitchen and floor rosters, service pace, complaints and reviews.
🏢 總部題：FY27 跨館店議題一頁摘要HQ: one-page FY27 cross-outlet brief
FY27 OGSM 規劃即將展開。請挑一個你部門會影響各館各店的議題（例如招募與人力、成本、系統導入、品牌行銷），用天雨傘寫一份給最高領導人的一頁摘要。想想：你的傘需要哪些館、店配合？
FY27 OGSM planning is about to start. Pick an issue from your department that affects hotels and restaurants (hiring, cost, systems, brand marketing…) and write a one-page brief for the top leader. Which outlets need to hold your umbrella with you?
寫完自我檢查：Self-check: ✔ 天有數字或具體觀察嗎？ ✔ 雨寫了兩種情境嗎？ ✔ 傘有人、有時間、有做法嗎？✔ Does the sky have numbers or concrete observations? ✔ Two kinds of rain? ✔ Does each umbrella have an owner, a date and a how?