Smart Soch, Better Business
Papa ke liye โ jinse maine business ki asli ABC seekhi. Aapne mujhe sikhaaya ki duniya kaise chalti hai. Ab meri baari hai kuch wapas dene ki. Yeh chhoti si bhet hai โ chai ke saath padhiyega. ๐
Saal 1943. World War II apne peak pe hai. America har hafte saikdon fighter planes bhej raha hai Europe mein โ Germany se ladne ke liye.
Lekin problem yeh hai ki bahut saare planes wapas nahi aa rahe. Ek mission pe 50 planes jaate hain, 35-40 wapas aate hain. Baaki? Khatam. Pilot bhi gaya, plane bhi gaya. America ke paas pilots bhi limited hain, planes bhi.
Military ke bade bade officers bethte hain meeting mein. Sawaal simple hai โ planes ko zyada mazboot kaise banayen? Armor lagao. Lekin armor lagaoge toh plane bhaari ho jaayega, slow udega, fuel zyada lagega. Toh POORE plane pe armor nahi laga sakte. Sirf sabse zaroori jagah pe lagana hai.
Toh unhone ek kaam kiya โ jo planes wapas aaye, unko examine kiya. Har goli ka nishaan count kiya. Map banaya โ kahaan kahaan goli lagi hai.
Pattern saaf tha. Fuselage pe โ yaani body pe โ bahut nishaan. Wings pe kaafi nishaan. Lekin engine pe? Bahut kam nishaan.
Generals ne kaha โ "Dekho, fuselage aur wings pe sabse zyada goli lag rahi hai. Wahaan armor lagao. Engine safe hai โ wahaan kam goli lagti hai."
Logical lagta hai na? Data hai, pattern hai, solution hai. Case closed.
Lekin ek aadmi tha โ Abraham Wald. Hungarian mathematician. Jewish tha โ Hitler ke aane pe Budapest chhod ke America bhaag aaya tha. Columbia University mein ek secret group mein kaam karta tha jo military ke liye maths ke problems solve karta tha. Chhota sa aadmi, mota chashma, hamesha chalk se blackboard pe likhta rehta tha.
Wald ne Generals ki baat suni. Phir bola โ "Aap bilkul ulta soch rahe ho."
Room mein sannata.
Wald ne samjhaya: "Aap sirf un planes ko dekh rahe ho jo WAPAS AAYE. In planes pe fuselage aur wings pe goli lagi โ AUR PHIR BHI yeh bach gaye. Matlab fuselage aur wings pe goli lagke bhi plane ud sakta hai. Yeh jagah itni khatarnak nahi hai."
"Ab socho โ engine pe nishaan kyun nahi dikh rahe? Kya isliye ki engine pe goli lagti hi nahi? Nahi. Isliye ki jinke engine pe goli lagi โ woh plane WAPAS HI NAHI AAYA. Woh crash ho gaya. Uska data tumhare paas hai hi nahi."
"Toh armor wahaan lagao jahaan NISHAAN NAHI HAIN โ engine pe. Kyunki wahaan goli lagne waala plane tumse milne hi nahi aaya."
Generals pehle toh chup rahe. Phir samjhe. Phir armor lagaya โ engine pe.
Result? Zyada planes wapas aane lage. Hazaaron pilots ki jaan bachi.
Ek mathematician ne, bina ek bhi plane udaaye, war ka course badal diya. Sirf isliye ki usne woh dekha jo DIKHTA NAHI THA.
Isko kehte hain Survivorship Bias โ "bach gaye walon ka dhoka."
Hum hamesha winners ko dekhte hain. Jo successful hai woh dikhta hai โ TV pe, newspaper mein, WhatsApp forwards pe. Ambani dikhta hai, Adani dikhta hai, Tata dikhta hai.
Lekin un HAZAARON logon ka kya jo same kaam karke, same mehnat karke, DOOB gaye? Woh kisi news mein nahi aate. Koi unka interview nahi leta. Woh "wapas nahi aaye" โ jaise woh planes.
Jab aap sirf successful logon ko dekhte ho, toh aapko lagta hai ki success ka formula simple hai โ mehnat karo, risk lo, bada socho. Lekin yeh toh woh log bhi kar rahe the jo fail hue. Fark kya tha? Woh aapko nahi dikhega โ kyunki woh data aapke paas hai hi nahi.
Wald ki seekh yeh hai: Jo NAHI dikhta โ woh zyada important ho sakta hai. Missing data pe dhyan do, sirf available data pe nahi.
Papa, ab isko apni duniya mein laate hain.
Aluminium pulveriser ka business socho. Aaj Delhi-NCR mein kitne log hain is line mein? 15-20 chalte honge acche se. Aap unhe jaante ho, unse compete karte ho, unse seekhte ho.
Lekin pichle 25 saal mein is business mein kitne log AAYE aur CHALE GAYE? Main bet lagata hoon 50 se zyada. Kisi ne plant lagaya, 2-3 saal chalaya, loss hua, band kar diya. Woh "wapas nahi aaye." Aap unhe dekhte nahi kyunki woh ab is market mein hain hi nahi.
Lekin unki galtiyon mein SABSE BADA SABAK hai. Kyun band hue? Quality control nahi tha? Pricing galat thi? Customer retain nahi kar paaye? Credit de de ke phase gaye? Yeh answers aapke kaam ke hain โ lekin yeh data aapko naturally nahi milega, kyunki fail hue log apni kahani sunate nahi phirte.
Gujarat mein lead smelting plant ki baat ho rahi hai. Toh plant visit karo, numbers dekho โ yeh toh karoge hi. Lekin EK KAAM AUR KARO: puch-taach karo ki is area mein pichle 10 saal mein kitne lead plants BAND hue. Kyun band hue? Pollution board ne notice diya? Raw material ki supply ruk gayi? Market ne price tod diya? Power supply unreliable thi?
Yeh woh planes hain jo wapas nahi aaye. Unki kahani sunoge toh armor sahi jagah lagega.
Export business mein bhi yahi hai. Aapke dost ka sprinkler network 20 countries mein hai โ aur aapko dikhega ki "dekho, yahan chal raha hai, wahaan chal raha hai." Lekin sawaal poocho โ kitne exporters ne in countries mein TRY kiya aur HAARE? Customs mein maal phasa? Payment nahi aayi? Quality rejection ho gayi? Unki galtiyon se seekhna FREE KA MBA hai.
Jo dikhta hai woh poori kahani nahi hai โ jo NAHI dikhta, wahaan asli sabak chhupa hai. ๐ฏ
America mein kuch researchers ne ek study ki. Simple si baat thi โ har saal Americans ka average weight badh raha hai. Data 20 saal ka tha. Graph banaya toh seedhi line upar ja rahi thi.
Ab researchers ne woh kiya jo researchers karte hain โ line ko AAGE tak kheench diya. Agar yeh rate jaari raha, toh 2048 tak kya hoga?
Jawab aaya: 2048 tak 100% Americans overweight ho jayenge.
Sau percent. Har ek insaan. Ek bhi patla nahi bachega. Nahin babies, nahin athletes, nahin models โ sab mote.
Sunne mein thoda funny lagta hai na? Lekin jab yeh study publish hui, toh logon ne seriously liya. News channels pe aayi. "America ka future!" "Health crisis!" Headlines bane.
Lekin zara RUKO aur socho.
Kya yeh physically POSSIBLE hai ki 100% log overweight hon? Kya koi bhi insaan โ chahe woh marathon runner ho, chahe woh 5 saal ka bachcha ho โ mota hoga? Common sense kehta hai โ nahi ho sakta.
Toh galti kahaan hui?
Galti yeh hui ki unhone seedhi line kheench di aur MAAN LIYA ki yeh hamesha seedhi hi jaayegi.
Lekin real life mein seedhi line hoti hi nahi. Har cheez jo badhti hai โ ek point pe slow hoti hai, rukti hai, ya ghat-ti hai. Yeh nature ka rule hai.
Ped ko socho. Ek naya paudha lagaate ho โ pehle saal 2 foot badha, doosre saal 2 foot aur. Toh kya 50 saal mein 100 foot ka ho jaayega? Nahi na! 20-25 foot pe ruk jaata hai. Growth curve hoti hai, seedhi line nahi.
Paani garam karo โ temperature seedhi line mein badhta hai 100ยฐC tak. Phir? Ruk jaata hai. Seedhi line KHATAM. Kitna bhi gas jalao, 100 se upar nahi jaayega (normal pressure pe).
Duniya curves mein chalti hai. Seedhi line sirf maths ki copy mein hoti hai.
Isko kehte hain Linearity Trap โ seedhi line ka dhoka.
Humaara dimaag patterns dhundhta hai. Jab 3-4 points ek line mein aate hain, toh dimaag TURANT seedhi line kheench deta hai aage tak. "Yeh toh badhta hi jaayega!" ya "Yeh toh girta hi jaayega!"
Lekin reality mein bahut kam cheezein seedhi line follow karti hain. Zyaadatar cheezein S-curve follow karti hain โ pehle slow, phir tez, phir phir slow, phir flat. Ya phir cycle follow karti hain โ upar, neeche, upar, neeche.
Jab koi aapko seedhi line graph dikhaye aur bole "dekho, yeh hoga future mein" โ toh PEHLA sawaal yeh poochho: "Kya yeh hamesha aise hi chalta rahega? Ya ek point aayega jab yeh rukega ya palat-ega?"
99% baar, answer hoga โ haan, palat-ega. Seedhi line KABHI hamesha seedhi nahi rehti.
Papa, yeh galti business mein ROZI karte hain log.
Aluminium ka price socho. January mein 200 tha, February mein 210, March mein 220. Aapke aas paas log kehne lagte hain โ "Bhai, stock kar lo! April mein 230 hoga, June tak 250!"
Seedhi line kheench di na? Lekin aluminium ka price kabhi seedhi line mein chala hai kya? Kabhi nahi. Upar jaata hai, phir China ne production badhaayi, suddenly neeche. Ya dollar strong hua, import sasta ho gaya, price gira. Ya demand slow hui, inventory badh gayi, price flat.
Main aapko ek aur example deta hoon. Aapka ek customer hai โ pichle 3 saal se har saal 10% zyada order de raha hai. Toh kya aap maan lo ki agle 10 saal bhi 10% badhega? Uski bhi capacity hai, uska bhi market hai. Ho sakta hai agle saal flat ho jaaye. Ho sakta hai woh doosra supplier dhundh le.
Export mein toh yeh aur dangerous hai. Ek country se pehle saal 5 lakh ka order aaya, doosre saal 10 lakh ka, teesre saal 20 lakh ka. Seedhi line kheencho toh lagta hai chauthe saal 40 lakh ka aayega. Lekin beech mein government ne import duty badha di โ toh ZERO. Seedhi line se ZERO pe aa gaye.
Gujarat ki lead plant mein bhi โ aaj lead ka price acha hai. Lekin aaj ka price dekh ke FUTURE ka investment mat karo. 10 saal ka graph dekho. Lead ka price kitni baar upar gaya aur kitni baar toota? Kitni baar logon ne socha "ab toh bas badhega" aur kitni baar market ne ulta maara?
Seedhi line pe bharosa karna โ yeh sabse mehnga dhoka hai business mein.
Jo aaj badh raha hai woh hamesha nahi badhega โ duniya curves mein chalti hai, seedhi line mein nahi. ๐
Aapke paas ek letter aata hai. Kisi stockbroker ka hai โ aapne naam nahi suna kabhi. Letter mein likha hai: "Next week Reliance ka stock upar jaayega."
Aap sochte ho โ koi random letter hai, ignore karo. Lekin next week SACH MEIN Reliance upar chala jaata hai.
Doosre hafte phir letter aata hai: "Tata Steel neeche jaayega." Aap dekhte ho โ sach mein neeche gaya.
Teesra letter: "Infosys upar." Sahi nikla.
Chautha. Paanchwa. Chhatha. CHHE KE CHHE sahi.
Ab aapka dimaag kehta hai โ yeh toh GENIUS hai! Isko toh stock market ka formula pata hai! Aap phone karte ho. Woh kehta hai โ "Sir, mera premium advisory service hai. 5 lakh ki fees. Guaranteed returns."
Aap 5 lakh de dete ho. Kyun nahi doge โ 6 predictions, 6 sahi! Iska track record toh KAMAAL hai!
Lekin RUKO. Peeche se kya hua tha, woh suniye.
Pehle hafte usne 10,240 logon ko letter bheja. Aadhe ko likha "Reliance upar jaayega" โ 5,120 logon ko. Aadhe ko likha "Reliance neeche jaayega" โ baaki 5,120 ko.
Reliance upar gaya. Toh 5,120 logon ke liye woh sahi tha. Baaki 5,120? Unko bhool jao. Unhe next letter nahi gaya.
Doosre hafte โ un 5,120 mein se aadhe ko kaha "Tata Steel upar", aadhe ko "neeche." Phir se โ jo sahi nikla unhe next letter.
Toh dekho kya hua:
Round 1: 10,240 โ 5,120 sahi
Round 2: 5,120 โ 2,560 sahi
Round 3: 2,560 โ 1,280 sahi
Round 4: 1,280 โ 640 sahi
Round 5: 640 โ 320 sahi
Round 6: 320 โ 160 sahi
160 logon ke liye yeh aadmi CHHE KE CHHE baar sahi tha. Unhe lagta hai yeh stock market ka Bhagwan hai. 160 mein se 10 bhi 5 lakh dein โ toh 50 lakh ka dhanda. Bina kisi knowledge ke. Bina kisi research ke.
Sirf MATHS ka jaadu.
Usne koi prediction nahi ki thi. Usne sirf itne zyada log ko letter bheja ki kuch toh sahi niklenge hi. Phir galat walon ko drop kiya. Jo bache โ unhe laga ki yeh genius hai.
Baltimore Stockbroker kehte hain isko. Kyunki pehli baar yeh trick Baltimore mein pakdi gayi thi.
Yeh wahi Survivorship Bias hai โ Lesson 1 ka cousin bhai โ lekin yahan ek naya twist hai: koi JAANBOOJHKE aapko sirf winning side dikha raha hai.
Jab koi apna track record dikhaye, toh pehla sawaal yeh hona chahiye โ "Yeh track record KITNE logon mein se chuna gaya hai?"
Agar 100 mutual fund managers hain aur 10 saal baad aap dekhte ho ki 3-4 ne market se better kiya โ toh kya woh genius hain? Ya sirf un 100 mein se statistically kuch toh sahi nikal hi aate?
Jab itne saare log try kar rahe hain, toh kuch ka result ZAROOR acha aayega โ by pure luck. Problem tab hota hai jab hum un lucky few ko dekh ke sochte hain ki unke paas koi special formula hai.
Asal test yeh hai โ kya woh AAGE BHI consistently sahi nikal sakta hai? Past performance future ka guarantee KABHI nahi hoti.
Papa, ab business mein isko dekhte hain.
Ek naya supplier aata hai aapke paas. Kehta hai โ "Sir, mere paas 3 clients hain, teeno khush hain. Yeh raha unka feedback." Bahut impressive lagta hai.
Lekin sawaal yeh hai โ usne kitne clients ko supply ki thi TOTAL? Agar usne 20 clients ko supply ki, 17 naraz hue, 3 khush rahe โ toh woh 3 dikhayega na! Woh 17 ka koi zikr nahi karega. Yeh Baltimore Stockbroker ka trick hai โ sirf jeetne waali side dikhao.
Property dealers mein yeh bahut hota hai. "Sir, Rajesh ji ne yahan plot liya tha, 2 saal mein double ho gaya!" Theek hai โ lekin us colony mein AUR kitne logon ne plot liya? Unka kya hua? Kya sabka double hua? Ya sirf Rajesh ji ka timing sahi tha aur baaki abhi bhi wait kar rahe hain?
Export agents bhi yahi karte hain. "Sir, humne Ghana mein 50 lakh ka deal karwaya ek client ko!" Bahut acha. Lekin kitne clients ko try karwaya total? 20 mein se 1 successful โ toh woh 1 dikhayenge. Baaki 19 ka invoice aaj bhi pending hai.
Aapke liye RULE yeh hona chahiye: Jab koi past performance dikhaye, toh poochho โ "Yeh kitne mein se hai?" Agar woh na bataye โ toh samajh jaao ki stockbroker ka letter aa raha hai. ๐
Aur haan โ apne aap pe bhi apply karo yeh. Aapne bhi 100 decisions liye honge business mein. 10 bahut ache nikle. Jab aap kisi ko apni kahani sunaate ho, toh kya woh 10 hi sunaate ho? ๐ Hum sab apne aap ke stockbroker hain thoda bahut.
Jab koi apna track record dikhaye, poocho โ "Yeh kitne mein se hai?" Jaadu mein trick hoti hai, genius mein nahi. ๐
Yeh kahani sunoge toh hasoge bhi aur sochoge bhi.
2009 mein ek neuroscientist tha โ Craig Bennett. Woh apne lab mein fMRI machine use karta tha โ brain scan karne waali machine, bahut mehengi, crores ki.
Ek din usne ek experiment kiya. Usne machine mein ek Atlantic Salmon rakha โ ek badi machli. Machli ko photos dikhaaye โ logon ke chehere, alag alag emotions ke saath. Phir scan kiya ki machli ka brain kya react kar raha hai.
Ab twist yeh hai โ MACHLI MAR CHUKI THI. Dead. Completely dead. Bazar se kharidi thi. Jo machli aap fry karke khaate ho โ waisi.
Results aaye. Aur results mein kya dikha? BRAIN ACTIVITY. Ek dead machli ke brain mein scan ne activity dikhaai โ jaise woh sach mein photos dekh ke react kar rahi ho!
Kya machli ka bhoot tha? Kya dead fish socch rahi thi? Nahi bhai. ๐
Hua yeh ki fMRI machine brain ko hazaaron chhote chhote hisson mein todti hai โ "voxels" kehte hain. Har voxel mein check karti hai ki activity hai ya nahi. Ek normal brain mein 130,000 se zyada voxels hote hain.
Ab agar aap 130,000 baar koi bhi test karo โ toh KUCH TOH positive aayega sirf BY CHANCE. Jaise agar aap 130,000 baar coin flip karo, toh kahin na kahin 10 heads ek saath aa jayenge. Iska matlab yeh nahi ki coin biased hai โ itne tests mein kuch toh "interesting" dikhega hi.
Yahi hua. Itne saare voxels test kiye ki kuch mein randomly "activity" dikh gayi. Machine ne report kar diya โ "Brain activity detected!" Lekin woh sirf noise thi โ random chance โ koi real signal nahi tha.
Craig Bennett ne yeh experiment ISLIYE kiya tha ki bataye ki bahut saare brain research papers mein yahi galti ho rahi hai. Log hazaaron tests karte hain, kuch positive results dhundh lete hain, aur paper publish kar dete hain โ "Humne discover kiya ki brain ka yeh hissa pyaar control karta hai!" Ya "Yeh hissa creativity ka hai!"
Lekin actually woh sirf dead fish waala result tha โ random noise ko real signal samajh liya.
Bennett ko is paper ke liye Ig Nobel Prize mila โ woh prize jo funny lekin important research ko diya jaata hai. Aur aaj bhi neuroscience mein log is paper ka reference dete hain jab koi bina sahi statistical correction ke paper publish karta hai.
Isko kehte hain Multiple Comparisons Problem โ ya simple mein, "itne test karoge toh kuch toh sahi niklega."
Socho aise โ aap ek coin flip kar rahe ho. Heads aaye toh aap kehte ho "yeh coin special hai." Ek baar heads aaye โ ho sakta hai chance ho. Do baar โ shayad chance. Lekin 10 baar lagaataar? Tab lagega ki haan, kuch toh hai.
Lekin AGAR aap 1000 alag alag coins ek ek baar flip karo โ toh kya kisi mein heads aayega? Obviously! Bahut saalon mein aayega! Iska matlab yeh nahi ki woh coin special hai.
Yahi galti hoti hai jab aap bahut saare tests karte ho aur phir sirf BEST result pick karte ho. Result real nahi hai โ sirf itne saare mein se ek toh acha nikal hi aata hai.
Isko samajhne ka ek aur tarika: Agar aap roz apna lucky number check karo newspaper mein โ toh saal mein 2-3 baar match ho jaayega. Iska matlab yeh nahi ki aapke paas psychic powers hain. Itne tests mein kuch toh match hoga hi.
Papa, yeh business mein BAHUT hota hai. Aur bahut mehenga padta hai.
Socho โ aap 20 suppliers ko ek chhota test order dete ho. Ek mahine baad dekhte ho โ 19 ne average kaam kiya, lekin EK ne kamaal ka maal diya. Bilkul perfect quality, time pe delivery, sab kuch.
Kya aap us ek ko select karke bada order de doge? Bahut log de dete hain.
Lekin RUKO. Agar aapne 20 suppliers test kiye, toh EK TOH acha niklega hi โ by pure chance! Ho sakta hai uska worker us din zyada dhyan de raha tha. Ho sakta hai maal ka batch acha tha. Ho sakta hai sirf LUCK thi.
Ek test se faisla mat karo. Kam se kam 2-3 test orders do USSE HI phir se โ dekhoo ki consistently acha hai ya sirf ek baar kamaal hua tha.
Export mein bhi yahi hota hai. Aap 10 countries mein samples bhejte ho. 9 se kuch nahi hua, lekin ek se order aa gaya. "Yeh toh GOLDMINE hai!" โ aur saara focus us ek country pe kar dete ho. Lekin ho sakta hai woh order sirf ek buyer ki personal zaroorat thi โ repeat nahi hoga.
Aluminium market mein bhi โ aap 5 naye alloys try karte ho market mein. Ek ki demand achi aayi. Kya woh sach mein market mein hit hai, ya sirf timing aur luck thi? 5 mein se 1 ka acha jaana statistical hai, guaranteed nahi.
Papa, RULE simple hai: Ek result pe kabhi bada faisla mat lo. Ek result dead fish ka brain scan ho sakta hai โ dikhta hai real, lekin hai sirf noise. Repeat karo, verify karo, PHIR vishwaas karo.
Itne test karoge toh kuch toh sahi niklega โ ek result pe bharosa mat karo, woh dead fish ka brain scan ho sakta hai. ๐
Lottery jeetna luck hai โ yeh toh sab jaante hain. Koi formula nahi hota. Hai na?
Galat.
2005 mein Massachusetts mein ek lottery thi โ "Cash WinFall." Normal lottery jaisi hi thi, lekin ek twist tha.
Jab jackpot ek certain amount tak pahunch jaata tha aur KISI NE nahi jeeta โ toh woh paisa neeche "roll down" hota tha chhote prizes mein. Matlab chhote matches jeetne walon ko zyada milta tha.
MIT ke kuch students โ maths ke nerds, 20-22 saal ke โ inhone yeh notice kiya. Aur unhone calculator nikaala.
Unhone har ticket ki value calculate ki. Normally ek $2 ki ticket ki expected value hoti hai lagbhag $0.80 โ matlab average mein aap har ticket pe $1.20 LOSE karte ho. Isliye lottery "tax on people who are bad at maths" kehlaati hai.
Lekin ROLL DOWN ke din? Jab jackpot neeche aata tha? Tab ek $2 ticket ki expected value $5.50 tak pahunch jaati thi.
MATLAB: Har $2 ki ticket pe AVERAGE $5.50 wapas milta. Har ticket pe $3.50 ka PROFIT.
Yeh lottery nahi rahi โ yeh INVESTMENT ban gayi.
MIT ke students ne ek group banaya โ "Random Strategies LLC." Unhone paise ikatthe kiye. Aur jab bhi roll down wala din aata, woh HAZAARON tickets khareedte the. 100,000, 200,000 tickets ek baar mein.
Kya har ticket jeetni thi? Nahi. Bahut saari khaali jaati thi. Lekin AVERAGE mein โ itne saare tickets kharidne pe โ maths unke favour mein tha.
Results? 7 saal mein unhone lagbhag $8 MILLION jeeta. After tax, after expenses โ solid profit.
Aur woh akele nahi the. Ek aur group tha โ ek retired couple, Gerald aur Marjorie Selfridge. 70+ saal ke. Michigan se drive karke Massachusetts aate the โ SIRF lottery tickets kharidne. Unhone bhi millions kamaye.
State lottery commission ko PATA tha ki yeh ho raha hai. Lekin technically koi rule nahi tod raha tha. Tickets koi bhi khareed sakta hai, jitni chahe.
Finally 2012 mein Massachusetts ne Cash WinFall BAND kar diya. Kyunki lottery ka purpose tha aam logon ko thoda bahut paisa dena โ naki maths ke students ko crorepati banana.
Lekin tab tak MIT waale apna paisa bana chuke the. Maths se. Calculator se. Koi luck nahi, koi trick nahi โ sirf EXPECTED VALUE ka formula.
Yeh concept hai Expected Value โ aur yeh SABSE useful maths concept hai business ke liye.
Formula simple hai:
Expected Value = (Jeetne ka amount ร Jeetne ki probability) โ (Haarne ka amount ร Haarne ki probability)
Agar EV positive hai โ deal acha hai, karo.
Agar EV negative hai โ deal bura hai, mat karo.
Normal lottery mein EV negative hota hai. $2 lagao, average mein $0.80 milta hai. LOSS. Isliye smart log lottery nahi khelte.
Lekin MIT walon ne woh RARE moment dhundha jab EV positive ho gaya. Tab lottery khelna SMART tha, stupid nahi.
Ek aur baat โ EV tab kaam karta hai jab aap BAHUT BAAR same decision lo. Ek baar lottery ticket loge toh kuch bhi ho sakta hai โ jeet bhi sakte ho, haar bhi. Lekin 100,000 baar loge toh result AVERAGE ke paas aayega. Isliye MIT walon ne hazaaron tickets lie โ ek do nahi.
Business mein bhi aap roz decisions lete ho. Har ek decision ek "ticket" hai. Agar aap consistently positive EV decisions loge โ toh LONG TERM mein aap jeetoge. Har baar nahi, lekin overall? Zaroor.
Papa, yeh formula aapke HAR business decision pe lagta hai. Literally har ek pe.
Example 1 โ Gujarat ki lead plant:
Plant ki cost: โน2 crore.
Agar sahi chali (probability 60%): 5 saal mein โน5 crore ka profit.
Agar nahi chali (probability 40%): โน1.5 crore ka loss (kuch toh recover hoga).
EV = (5 crore ร 0.6) โ (1.5 crore ร 0.4) = 3 crore โ 60 lakh = โน2.4 crore POSITIVE.
Maths keh raha hai โ karo. Lekin SIRF tab jab aap risk afford kar sako. MIT walon ne SAARA paisa ek ticket pe nahi lagaya tha โ hazaaron pe lagaya tha. Aap bhi ek deal pe sab kuch mat lagao.
Example 2 โ Export deal:
Ek nayi country mein first shipment ka cost: โน10 lakh (samples, shipping, agent fees).
Agar order aaya (probability 30%): โน50 lakh ka annual business.
Agar nahi aaya (probability 70%): โน10 lakh gone.
EV = (50 lakh ร 0.3) โ (10 lakh ร 0.7) = 15 lakh โ 7 lakh = โน8 lakh POSITIVE.
Acha deal hai โ lekin EK country mein nahi, 5-6 countries mein try karo. Jaise MIT ne hazaaron tickets lie โ aap bhi multiple markets try karo. Sab mein nahi chalega, lekin AVERAGE mein aap plus mein rahoge.
Example 3 โ Daily decision:
Ek naya customer credit maang raha hai. โน5 lakh ka maal chahiye, 90 din ki credit.
Agar pay kiya (probability 80%): โน75,000 profit.
Agar nahi pay kiya (probability 20%): โน5 lakh loss.
EV = (75,000 ร 0.8) โ (5,00,000 ร 0.2) = 60,000 โ 1,00,000 = โน40,000 NEGATIVE.
Maths keh raha hai โ MAT DO credit. Ya phir chhota amount do, ya advance lo.
Papa, yeh formula simple hai lekin POWERFUL hai. Har deal mein do minute lagao โ "kitna milega, kitni chance, kitna jayega, kitni chance." Calculator pe karo. Jo positive aaye โ karo. Jo negative aaye โ chhodo ya terms badlo.
MIT ke students lottery mein yeh karte the. Aap business mein karo. Same formula, same logic, BAHUT bada result.
Har deal mein yeh poocho: 'Kitna milega ร kitni chance' MINUS 'kitna jayega ร kitni chance' โ positive hai toh karo, negative hai toh chhodo. ๐ฐ
George Stigler. Nobel Prize winner. Economics ka badshah. Ek baar unse kisi ne poocha โ "Sir, aapki life ka sabse best advice kya hai?"
Unhone kaha โ "Agar tumne zindagi mein kabhi flight miss nahi ki, toh tum airport pe bohot zyada time waste kar rahe ho."
Suno yeh dhyan se, kyunki yeh sunne mein pagalpan lagta hai.
Hum sab kya karte hain? Flight 2 baje hai toh 11 baje ghar se nikal jaate hain. "Traffic hogi... security line lamba hoga... gate dhundhna padega..." Phir kya hota hai? 12:15 pe airport pahunch jaate hain. Security 10 minute mein clear. Gate pe baith ke 1 ghanta 45 minute phone scroll karte hain. Boring. Bekaar. Time barbad.
Par hum khush hain! Kyunki flight miss nahi hui. "Dekho, time pe pahunch gaye!"
Ab Stigler ka point samjho. Saal mein 20 baar fly karte ho. Har baar 2 ghante extra dete ho "just in case." Saal mein 40 ghante โ matlab POORE 5 din โ sirf airport pe wait karne mein gaye. 5 din! Ek chhoti si vacation ka time.
Agar aap thoda risk lete โ 1 ghanta pehle nikalte โ toh 19 flights pakad lete aur 1 miss hoti. Par 20 ghante bach jaate. Woh 20 ghante mein aap kya kar sakte the? Ek naya client mil sakta tha. Ek deal close ho sakti thi. Bache ke saath time spend kar sakte the.
Stigler keh rahe hain โ PERFECT record bohot mehenga hai. Perfection ka price bohot zyada hai. Thoda imperfect hona actually SMART hai.
Yeh sunne mein ulta lagta hai na? Par yahi toh maths ki khoobsurti hai โ kabhi kabhi jo galat lagta hai, wahi sahi hota hai.
Is concept ko economists "optimization" kehte hain. Simple bhasha mein โ TOTAL picture dekho, sirf ek cheez mat dekho.
Socho aise โ aap roz subah dukaan kholte ho. Agar aap KABHI late nahi hote, toh iska matlab hai aap har roz 1 ghanta pehle jaate ho. Saal mein 365 ghante extra. Kya woh 365 ghante ka koi value nahi hai?
Par agar aap kabhi kabhi 10 minute late kholen, toh kya hoga? Shayad 2-3 customer miss honge. Par 300+ ghante bach jayenge.
Yeh trade-off hai. Zero risk = maximum waste. Thoda risk = overall better result.
Perfection ek jaanwar hai jo aapka time kha jaata hai. Smart log perfect nahi hote โ woh OPTIMAL hote hain. Matlab โ sab kuch milake sabse achha result kya hai, woh dekhte hain.
Papa, ab apni duniya mein socho.
Aapne 30+ saal business kiya. Kitni deals mein loss hua? Agar jawab hai "bohot kam" ya "almost kabhi nahi" โ toh ek second ruko.
Iska matlab yeh NAHI hai ki aap bohot achhe ho. Iska matlab yeh hai ki aapne bohot saari ACHHI deals ko "nahi" bol diya kyunki thoda risk tha.
Gujarat ka lead smelting plant yaad hai? Risky lagta hai โ naya market, nayi jagah, alag logistics. Par agar aap sirf SAFE deals karte rahe โ sirf aluminium, sirf Delhi, sirf purane customers โ toh 10 saal baad bhi wahin khade hoge.
Export business ka socho. Pehli 2-3 shipments mein kuch gadbad hogi. Payment delay hoga. Koi container mein quality issue aayega. Ek customer complaint karega. Aur aap sochoge โ "Yeh export ka chakkar galat kiya."
Par NAHI! Woh 2-3 misses toh honi hi thi. Woh tuition fees hain. Agar 20 mein se 17 shipments sahi gayin, toh aap PROFIT mein ho โ paisa mein bhi aur seekh mein bhi.
Jo businessman kabhi haara nahi, usne kabhi khela hi nahi. Stigler ki flight miss karo. Kuch deals miss hongi. Par OVERALL aap bohot aage nikloge.
Jo kabhi haara nahi, usne kabhi seriously khela hi nahi. โ๏ธ
Ek sawaal. Har ladki se poocho โ "Achhe dikhne wale ladke kaise hote hain?" Zyaadatar yahi bolegi โ "Arrogant. Badtameez. Apne aap mein ghuse rehte hain."
Aur phir poocho โ "Achhe insaan wale ladke kaise dikhte hain?" Jawab aayega โ "Average. Simple. Looks mein kuch khaas nahi."
Toh lagta hai โ duniya mein ek rule hai. Handsome = Jerk. Nice = Ugly. Dono ek saath kabhi milte hi nahi.
Par RUKO. Yeh sach nahi hai. Yeh ek mathematical illusion hai. Aur iska naam hai Berkson's Paradox.
Samjho kaise kaam karta hai.
Ek ladki date karne ke liye ladka choose karti hai. Woh kisko haan bolegi? Sochne ki zaroorat nahi โ do mein se ek quality chahiye. YA toh bohot achha dikhta ho (toh average nature chalega), YA bohot achha insaan ho (toh average looks chalenge).
Ab uska dating pool dekho. Ismein kaun kaun hai?
๐ Handsome par nature mein average โ unhe looks ki wajah se entry mili.
๐ Average dikhne wale par BOHOT achhe insaan โ unhe personality ki wajah se entry mili.
Aur kaun NAHI hai is pool mein? Handsome + Nice ladke! Kyun? Kyunki woh toh pehle se kisi ke saath hain โ unhe toh dono qualities mil gayi, market mein zyada der tike hi nahi!
Toh ladki ka experience kya kehta hai? "Maine jo handsome ladke date kiye โ sab bure nikle. Jo achhe the โ sab average dikhte the." Uska conclusion โ looks aur nature OPPOSITE hain.
Par bahar duniya mein? Koi connection hi nahi hai dono mein! Bohot handsome aur bohot achhe log bhi hain. Bas uske SAMPLE mein nahi aaye.
Yeh hai Berkson's Paradox โ jab aap cheezein FILTER karte ho, toh jo pattern dikhta hai woh REAL nahi hota. Woh aapke filter ka shadow hai.
Berkson's Paradox tab hota hai jab aap kisi group ko do mein se EK quality ke basis pe select karte ho. Isse aapko lagta hai ki dono qualities ek doosre ke AGAINST hain โ par asal mein woh independent hain. Unka koi connection nahi hai.
Ek aur example socho. Log kehte hain โ "Jo restaurants achha khaana dete hain, unki service buri hoti hai. Jo service achhi dete hain, unka khaana average hota hai."
Kyun? Kyunki aap restaurant tab jaate ho jab YA toh khaana famous ho YA service famous ho. Jo dono mein average hai โ usmein aap jaate hi nahi. Toh aapke experience mein โ khaana aur service OPPOSITE lagte hain.
Par reality mein? Bohot restaurants hain jo dono achha dete hain. Bas aapne dhundhe nahi.
Filter hatao. Poori picture dekho. Tab sach dikhega.
Papa, ab apne aluminium market mein socho. Yeh BILKUL wahi trap hai.
Aap supplier kaise choose karte ho? Simple โ do mein se ek chahiye. YA toh SASTA de, YA ACHHI quality de. Dono mein se ek milna chahiye warna deal nahi.
Ab aapka 30 saal ka experience kya kehta hai? "Sasta maal = kharab quality. Achhi quality = mehenga." Yeh aapko PAKKA lagta hoga. Aapne hazaaron baar dekha hai.
Par ruko โ yeh Berkson's Paradox hai!
Aapke supplier pool mein kaun hai? Woh jo YA toh price pe jeete YA quality pe. Jo dono mein AVERAGE hai โ woh aapke radar pe aaya hi nahi. Aapne unse deal ki hi nahi.
Aur jo sasta BHI deta hai aur achha BHI โ woh itna popular hai ki uske paas capacity nahi hai naye customers ke liye. Ya phir woh kisi aur state mein hai โ Gujarat mein, Rajasthan mein โ jahan aapne dhundha nahi.
Export market mein yeh aur bhi important hai. Aap sochoge โ "Achhe international buyers late payment karte hain" ya "Jo advance deta hai woh chhota buyer hai." Par yeh aapke LIMITED sample ka sach hai. Duniya bohot badi hai.
Agle baar jab aapko lage โ "Yeh do cheezein kabhi saath nahi milti" โ toh apne aap se poocho: Kya yeh DUNIYA ka sach hai, ya MERE filter ka sach hai?
Aapka experience galat nahi hai โ aapka sample galat hai. Duniya aapke filter se badi hai. ๐
1933 ki baat hai. Horace Secrist naam ke ek economics professor ne 10 SAAL mehnat ki. Data ikkattha kiya. Graphs banaye. Calculations kiye. Phir ek moti si kitaab likhi โ "The Triumph of Mediocrity in Business."
Uski discovery kya thi? GROUNDBREAKING thi uske hisaab se.
Usne America ki top companies dekhi โ jo 1920 mein sabse zyada profitable thi. Phir 10 saal baad dekha. Kya hua? Unka profit GIR gaya tha. Average ki taraf aa gayi thi.
Phir usne WORST companies dekhi โ jo 1920 mein sabse zyada loss mein thi. 10 saal baad? Unka performance SUDHAR gaya tha. Woh bhi average ki taraf aa gayi thi.
Secrist ne badi proudly likha โ "Dekho! Business mein mediocrity jeet ti hai! Sab average ki taraf jaate hain!"
Kitaab publish hui. Reviews aaye. Aur phir... statisticians ne usse mazaak bana diya.
Kyun? Kyunki yeh koi DISCOVERY nahi thi. Yeh toh maths ka ek basic rule hai โ jo har bachha samajh sakta hai.
Socho aise. Class mein 50 bacche hain. Ek exam hua. Kuch bacchon ne BOHOT achha kiya โ 95, 98, 100. Kya yeh bacche genius hain? Shayad. Par yeh bhi possible hai ki un bacchon ko LUCK mila โ jinke questions aaye woh unhe aate the, us din tabiyat achhi thi, wild guess sahi gaya.
Agla exam hota hai. Ab un "toppers" ko woh SAME luck milega? Nahi na! Toh unke marks girenge. Average ki taraf aayenge.
Aur jo bacche pehle exam mein fail hue โ shayad unka din kharab tha, shayad unhe galat topics padhe the. Agla exam mein unki luck average hogi โ toh marks sudhrega.
Yeh hai "Regression to the Mean." Extreme results mein LUCK ka bohot bada role hota hai. Aur luck REPEAT nahi karta. Toh extreme ke baad average aana NATURAL hai โ isme koi discovery nahi hai.
Bechara Secrist. 10 saal mehnat ki yeh prove karne ke liye ki paani garam karo toh bhap banti hai. ๐
Regression to the Mean ka rule simple hai โ jab bhi koi result EXTREME ho (bohot achha ya bohot bura), toh usmein luck ka bada haath hota hai. Aur kyunki luck bar bar SAME nahi hota, agla result average ki taraf aayega.
Ek aur example. Cricket mein koi batsman ek match mein 150 runs banata hai. Agla match? Zyaadatar 40-50 runs. Log kehte hain "form kharab ho gayi." Par nahi โ pehle match mein sab kuch PERFECT tha โ pitch, bowling, luck, mood. Woh combination roz nahi milta.
Iska ULTA bhi sach hai. Agar koi batsman 3 match mein zero maara, toh agle match mein achha khelne ke chances hain. Kyunki itna bura hona bhi luck chahta hai โ aur buri luck bhi repeat nahi karti.
Yeh samajhna bohot zaroori hai kyunki log HAMESHA extreme results ko permanent samajh lete hain. "Woh toh genius hai!" ya "Woh toh bekar hai!" Dono galat ho sakte hain.
Papa, yeh lesson aapke liye GOLD hai. Kyunki business mein hum yeh galti ROZZZ karte hain.
Scenario 1: Ek quarter mein record profit aaya. Aluminium ki demand achanak badh gayi. Export ka ek bada order aaya. Sab kuch click hua. Aap khush. Partners khush. Agle quarter ki expectation? "Aur zyada profit!"
Par RUKO. Woh record quarter mein kitna LUCK tha? Aluminium ka price upar tha โ aapke haath mein nahi tha. Woh export order ek referral se aaya โ repeat nahi hoga necessarily. Weather achha tha toh logistics smooth tha.
Agle quarter mein yeh sab SAME hoga? Nahi. Toh profit average ki taraf aayega. Yeh FAILURE nahi hai โ yeh MATHS hai.
Scenario 2: Ek quarter mein loss hua. Coke ki price badh gayi. Ek bada customer ne payment roka. Ek shipment damage hua. Sab kuch galat gaya. Aap panic mein. "Business doob raha hai!"
Par RUKO. Itna sab ek saath galat hona bhi UNUSUAL hai. Agle quarter mein sab kuch itna bura nahi hoga. Average ki taraf wapsi hogi.
Sabse bada lesson: Jab sab kuch achha chal raha ho โ humble raho. Luck hai. Jab sab kuch bura chal raha ho โ patience rakho. Luck badlegi.
Aur haan โ agar koi naya supplier pehle order mein AMAZING quality de, toh POORA business mat de do. Shayad pehla order special effort tha. Wait karo. 3-4 orders ke baad uska ASLI level dikhega โ average ki taraf aayega.
Record profit ke baad humble raho. Record loss ke baad patience rakho. Dono mein luck hai. ๐
Ek din aap doctor ke paas gaye. Routine checkup. Doctor ne kaha โ "Ek test karte hain, bas precaution ke liye."
Test hua. Report aayi. Doctor ka chehra thoda serious ho gaya.
"Dekhiye, test positive aaya hai. Par ghabraiye mat โ yeh test 90% accurate hai."
90% accurate! Aapka dil doob gaya. 90 mein se 90 baar sahi batata hai. Matlab โ 90% chance hai ki aap beemar ho.
Ghar aake aapne sabko bataya. Tension ho gayi. Raat ko neend nahi aayi. Google pe search kiya. Aur dar gaye.
Par RUKO. Ek minute maths karte hain. Kyunki maths aapko RAHAT dega.
Maan lo yeh bimari 1% logon ko hoti hai. Matlab 1000 logon mein se sirf 10 log SACH mein beemar hain.
Ab 1000 logon ka test karo:
๐ 10 log jo SACH mein beemar hain โ unme se 90% ka test positive aayega. Matlab 9 logon ka positive.
๐ 990 log jo beemar NAHI hain โ unme se 10% ka test GALAT positive aayega (kyunki test 100% accurate nahi hai). 10% of 990 = 99 logon ka false positive.
Total positive results: 9 + 99 = 108.
Ab sawaal โ 108 positive results mein se kitne log SACH mein beemar hain? Sirf 9.
9 out of 108 = lagbhag 8%.
AAPKA test positive aaya. Par aap beemar hone ka chance sirf 8% hai. 90% nahi!
Yeh sunke dimag ghoom gaya na? 90% accurate test, positive result, phir bhi sirf 8% chance?
Haan. Kyunki ek important cheez hai jo log BHOOL jaate hain โ BASE RATE. Matlab โ kitne logon ko yeh bimari HOTI hi hai?
Jab bimari rare hai, toh even ek achha test ZYAADATAR galat positive dega. Kyunki beemar logon se zyada healthy log hain jinpe test galti karega.
Yeh samajhna mushkil hai. Par yeh zindagi ki sabse important maths tricks mein se ek hai.
Is concept ko Bayesian Inference kehte hain. Thomas Bayes naam ke ek 18th century priest ne yeh socha tha.
Simple rule yeh hai: Kisi bhi information ka matlab tab tak ADHURA hai jab tak aap BASE RATE nahi jaante.
Base rate = woh cheez kitni COMMON hai.
Ek aur example. Koi aapko bole โ "Mere paas ek machine hai jo nakli note 95% baar pakad leti hai." Achha lagta hai na? Par poocho โ 1 lakh notes mein kitne nakli hote hain? Agar 100, toh machine 95 pakdegi. Par 99,900 asli notes mein se 5% โ matlab 4,995 โ ko GALAT se nakli bolegi!
Toh machine jab bhi "nakli" bole, zyaadatar woh GALAT hogi.
Base rate pooche bina koi bhi accuracy ka number MEANINGLESS hai.
Papa, yeh lesson business mein SABSE important hai. Har jagah yeh trap hai.
Scenario 1: Koi consultant aake bole โ "Mere 90% clients ko profit hua hai. Aap bhi kariye yeh investment."
Pehla sawaal โ "Kitne logon ne OVERALL yeh investment ki aur kitne mein profit hua?" Agar 1000 logon ne ki aur sirf 50 mein profit hua, toh consultant ke 90% ka matlab KUCH nahi. Woh apne cherry-picked clients dikha raha hai.
Scenario 2: Gujarat ka lead smelting plant. Koi aake bole โ "99% sure hai yeh deal profitable hoga." Achha lagta hai. Par poocho โ "Aise kitne deals hote hain saal mein? Aur unme se kitne ACTUALLY profitable nikalte hain?"
Agar 100 mein se sirf 5 aise plants actually achha return dete hain, toh base rate 5% hai. Ab chahe koi 99% sure ho โ maths kehta hai abhi bhi risk bohot hai.
Scenario 3: Export market mein ek naya buyer mila. Uska reference achha hai. Payment history achhi hai. Sab kuch POSITIVE lag raha hai. Par poocho โ is country mein Indian suppliers ke saath kitne deals ACTUALLY smooth jaate hain? Agar base rate low hai, toh individual positive signals se mat beh jaao.
Hamesha poocho: "Yeh cheez OVERALL kitni baar kaam karti hai?" โ phir kisi ki guarantee ka value samjho.
Koi bhi bole "90% sure" โ pehle poocho "100 mein se kitne mein SACH mein hota hai?" ๐ฅ
1785. France. Revolution se kuch saal pehle. Marquis de Condorcet naam ka ek mathematician โ brilliant aadmi, freedom fighter, philosopher โ ek problem solve karne baitha.
Problem simple thi: Jab log group mein faisla karte hain, toh SAHI faisla hona chahiye na? Democracy ka poora concept isi pe tika hai โ majority sahi hoti hai.
Par Condorcet ne kuch aisa discover kiya jo uske hosh uda de.
Suno yeh kahani.
Teen partners hain ek business mein โ Rajesh, Suresh, aur Mahesh. Unhe decide karna hai ki company ka paisa kahan lagayein. Teen options hain:
๐ญ Plan X โ Naya plant lagao Gujarat mein
๐ฆ Plan Y โ Export business start karo
๐ฐ Plan Z โ Paisa FD mein rakho, safe khelo
Teen logon ki preference:
Rajesh: X sabse achha, phir Y, phir Z
Suresh: Y sabse achha, phir Z, phir X
Mahesh: Z sabse achha, phir X, phir Y
Ab voting karo.
X vs Y: Rajesh aur Mahesh โ dono ko X, Y se better lagta hai. Toh X jeeta. 2-1. โ
Y vs Z: Rajesh aur Suresh โ dono ko Y, Z se better lagta hai. Toh Y jeeta. 2-1. โ
Logic kehta hai โ agar X beats Y, aur Y beats Z, toh X ko Z ko bhi beat karna chahiye, haina?
X vs Z: Suresh aur Mahesh โ dono ko Z, X se better lagta hai. Z JEETA. 2-1. โ
KYA?!
X beats Y. Y beats Z. Par Z beats X!
Yeh aisa hai jaise โ Sharma ji Verma ji se achhe hain. Verma ji Gupta ji se achhe hain. Par Gupta ji Sharma ji se achhe hain. KAISE?!
Yeh koi trick nahi hai. Yeh koi special case nahi hai. Yeh MATHS ka proven truth hai โ jab 3 ya zyada options hon, toh group ki preference CIRCULAR ho sakti hai. Koi clear winner POSSIBLE hi nahi hai.
Condorcet ne yeh 1785 mein prove kiya. Aur tab se duniya ki har committee, har board meeting, har parliament is problem se ladh rahi hai.
Democracy ka dirty secret โ majority opinion EXIST hi na kare, yeh possible hai.
Condorcet's Paradox kehta hai โ individual preferences RATIONAL ho sakti hain, par group preference IRRATIONAL ho sakti hai.
Har ek partner apne aap mein sahi hai. Rajesh ka logic sahi. Suresh ka logic sahi. Mahesh ka logic sahi. Par teeno ko milao toh? Circular loop. Koi answer nahi.
Yeh isliye hota hai kyunki group preference ek REAL cheez nahi hai. Yeh ek illusion hai jo hum voting se create karte hain. Par voting system alag hota toh result alag aata.
Agar pehle X vs Y karo, phir winner vs Z โ toh Z jeetega.
Agar pehle Y vs Z karo, phir winner vs X โ toh X jeetega.
Agar pehle X vs Z karo, phir winner vs Y โ toh Y jeetega.
MATLAB โ koi bhi jeet sakta hai. Bas yeh matter karta hai ki voting ka ORDER kya hai! Jo agenda set kare, woh winner decide kare. Scary hai na?
Papa, yeh lesson har us din kaam aayega jab aap partners, family, ya team ke saath koi bada faisla karte ho.
Socho โ aap, aapka partner, aur aapka Gujarat wala contact โ teeno milke decide kar rahe ho ki lead smelting plant kaise chalayein.
Aap chahte ho โ pehle small scale mein start karo, phir badhao.
Partner chahta hai โ full investment karo, bada plant lagao.
Gujarat wala chahta hai โ pehle 6 mahine survey karo, phir decide karo.
Teen log. Teen plans. Voting karo toh kya hoga? Circular loop! Koi clear winner nahi.
Ab kya kare?
1๏ธโฃ Samjho ki "majority" hamesha sahi nahi hoti. 3 logon ki voting se BEST answer nahi aata โ bas EK answer aata hai jo voting system pe depend karta hai.
2๏ธโฃ Kabhi kabhi EK experienced insaan ka faisla better hai than committee ka. Agar aapko APNE experience pe bharosa hai โ toh woh vote se zyada valuable hai.
3๏ธโฃ Agar voting karni hi hai, toh CRITERIA pehle decide karo โ "Sabse kam risk wala plan" ya "Sabse zyada return wala plan." Jab CRITERIA fix ho, toh circular loop tootegi.
4๏ธโฃ Meetings mein dhyan do โ jo pehle bolta hai, woh agenda SET karta hai. Aur agenda set karne wala RESULT control karta hai. Toh meetings mein pehle bolo. Apna plan pehle rakho.
Democracy achhi hai. Par business mein โ kabhi kabhi dictatorship better hai. ๐
3 log, 3 raayein, voting se koi clear answer nahi โ kabhi kabhi EK experienced insaan ka faisla best hai. ๐ณ๏ธ
Papa,
Yeh 10 lessons maine aapke liye likhe hain. Koi textbook nahi hai yeh โ yeh woh cheezein hain jo MUJHE kisi ne nahi sikhayi thi, aur maine mushkil se seekhi.
Aap 30+ saal se business kar rahe ho. Aapne yeh sab apne EXPERIENCE se seekha hai โ bina kisi book ke. Maths ne sirf usse words diye hain.
Jab aapne mujhe chhote mein bataya tha โ "Beta, sab kuch dikhta hai waisa nahi hota" โ tab aap Berkson's Paradox sikha rahe the. Jab aapne kaha โ "Ek achha quarter dekhke mat uchlo" โ tab aap Regression to the Mean sikha rahe the. Jab aapne kaha โ "Pehle poori baat suno, phir bolo" โ tab aap Base Rate sikha rahe the.
Aapko maths ki zaroorat nahi thi. Par mujhe thi. Toh maine seekhi. Aur ab aapke liye likh di.
Bas itna yaad rakhna โ duniya mein sabse khatarnak cheez hai BHAROSA. Apne gut feeling pe bharosa, apne experience pe bharosa, numbers pe bharosa. Sab ka apni jagah hai. Par ANDHA bharosa โ woh galti hai.
Sochte raho. Sawaal karte raho. Hisaab lagao. ๐ฏ
โ SJ
๐ฒ Poora Article Share Karein