bz dm mdl - lecture 4

8/16/2019 Bz Dm Mdl - Lecture 4

http://slidepdf.com/reader/full/bz-dm-mdl-lecture-4 1/32

Lecture 4Business Decision-making

Models02033100

Shenzhen University

College of International ExchangeBachelor of Econo ics !

International "ra#eSource: Marina KotsianasUniversity of Southern California



Strategy$ SC%& 'ra e(or)Identify Q & Work Backwards



Story*telling "echni+ue



Synthesis&nalysis,esearch-ro.lestructuring

-ro.le#e/nition

S C %

+

+

+

+

+

++

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+#

&

ECEIssue "rue

#

The Minto PyramidPrinciple

Logic



Source: Structured Approach to Cases by Neal & Tanay Shah



-ractice$

3 e( or)

4 rlan#o

5 Silicon 6alley

7 anshan 8istrict

9 uevo Leon

10 "ai(an

11 :angna

12 "oronto



'ill*in*the*.lan)s

Source: Structured Approach to Cases by Neal & Tanay Shah



-ractice$ Letter fro 'rien#



I#entifying I ;ortant Info

• <ho= >?int$ 4@

• <hat= >?int$ 2@

• <hen= >?int$ 4@

• <here= >?int$ 2@

• <hy= >?int$ 3@

• ShirleyA LucyA Lucy s.fA Lucy s o

• I hate youA no longer(ant to .e your frien#

• Satur#ayA Sun#ayAyester#ayA #ay of letter

• at the ;ar)A at Lucy shouse

• )isse# y .oyfrien#Ainsulte# o s foo#A)ic)e# y cat



Structure# &nalysis



8ra( your o(n ;yra i#

%uestion$ =

Dey-oint 3

Dey-oint 2

Dey-oint 1

ain%uestion

,eason1 2

,eason1 1

,eason2 2

,eason2 1

&ns(er$

,eason3 1



Sa ;le Solution



I#eas can .e grou;e#

in#uctively or #e#uctively

In#uctive Logic

8e#uctiveLogic

“…and and !

“…plus plus !



Logic >1F2@ G In#uctive

Exa ;le$



Logic >2F2@ G 8e#uctive

Exa ;le$



<hy= <hy= <hy=



<hat are the course

goals=Learn

-ractice&;;ly



our In#ivi#ual &ssign ent

• PTI ! "#$ D% ' Wednesday( #pril)* th

• 6isit the Canton 'air in :uangzhou – Stage 1$ &;ril 15*19

• Intervie( 3 #iHerent exhi.itors$ ?o( #oesthis fair hel; your .usiness=



our In#ivi#ual &ssign ent• PTI ! "B$ D% ' Wednesday( May ++ th

• Use "he into -yra i# -rinci;le >SC%&@ to (rite

a case arguing ho( (oul# you select a university>in the US@ to stu#y for BachelorF aster #egree=

• Inclu#e #etails of .usiness ;ro.le or

o;;ortunityA inclu#ing costs an# .ene/ts of each;ossi.le solutionA an# your reco en#e#solution for a;;roval



utline1. Executive Summary

– Issue – Recommendation – Justification

2. Problem Definition – Problem statement – lternatives available – Summary of Preferred lternative

!. Recommended action

– "r#ani$ational Im%act – Im%act on &niversity mission and ot'er services – Ris(s – )ec'nolo#y *i#ration Plan

+. Pro,ect "vervie- %lan for t'e transformation – /oals and ob,ectives of transformation – Success metrics – *a,or Pro,ect *ilestones

0. ost enefit nalysis – Im%acts on revenue – Im%acts on costs – om%arisons -it' alternatives



8etails

• "his is an in#ivi#ual (riting assign ent – can (or) togetherA .ut su. it your o(n re;ort

• 10 ;ages >inclu#ing charts ! ta.les@ – 12 ;oint fontA 1 5 s;acing

• Su. it a har# co;y at the .eginning ofclass – late su. issions *10 ;er #ay



-olishe# ! -rofessional

• :ra ar an# s;elling atter G evenfor great i#eas

• "here are excuses for s;ellingista)es in to#ay s (orl#

• &voi# re;etition

• Use su.Ject hea#ers a;;ro;riately

22



23

Basics

• "hin) a.out your au#ience – <ho are they= >e g College 8ean or -resi#ent@

– <hy are they rea#ing this= – <hat #o they (ant to /n# out=

• a)e it easy for the



24

SourcesCitations an# references1 Use +uotes >K @ (hen you +uote

2 Use a nu .ering syste so that the rea#er can easily/n# the source of your infor ation

3 Using a .i.liogra;hy at the en# of your #ocu entAinclu#e the &uthorA #ateA title an# location of yoursource –

&n ht l a##ress is not suMcient G that L gives thelocation



25

a)ing a case for changea)e a structure# argu ent for your reco en#ation ?ere isa goo# techni+ue for ;ersuasive (ritingA )no(n as the into

-yra i# -rinci;le$S$ Situation G <here are (e no(C$ Co ;lication G <hat has change#%$ %uestion G <hat shoul# (e #o=&$ &ns(er G <e nee# to

"his techni+ue can .e use# for s;eechesA #ocu entsA;resentationsA etc

"hese are " section hea#ers G an# often (or) .etterintegrate# su.tly



S$ Situation

• Shoul# .e so ething everyone agrees on• Esta.lishes that you )no( (hat you are

tal)ing a.outA an# the relevance of the

situation• 'actsA not o;inions

Exa ;le$ Na;an is one of the (orl# s largest

econo ies &;;roxi ately 30 of their;o(er co es fro nuclear ;o(er ;lants

27



C$ Co ;lication

• So ething has ha;;ene# to u;set the status+uo

• & recent event or #iscovery• "he au#ience shoul# instantly see that is

raises a +uestion

Exa ;le$& assive earth+ua)e then resulting tsuna i

have cause# #a age to so e of Na;an snuclear ;lants "he fallout ay cost livesan# environ ental #a ageA an# (ill #a agecon/#ence in nuclear ;o(er

2O



%$ %uestion

• "he +uestion shoul# .e o.vious frothe co ;lication

• "his shoul# lea# to an ans(er

Exa ;le$?o( shoul# Na;an ;lan for an

econo icalA safe energy future=2P



&$ &ns(er

• "he ans(er is your ain ;oint• Su arize /rstA then .rea) #o(n to #etails• "he ain .o#y shoul# all su;;ort this

ans(er

Exa ;le$ Na;an shoul# .uil# 50 foot (alls aroun# theirnorthern coastlineA (hile investing ingeother al ;o(er stations for energy gro(th

29



Logical &rgu ents

• our ans(er shoul# actually a##ress the+uestion that (as as)e#

• Start (ith the ain ;oint an# .rea) #o(nthe ;arts of it

“"apan should build #$ foot %alls around theirnorthern coastline %hile investin' in'eother(al po%er stations for ener'y

'ro%th! – <hy 50 feet= – <hy northern= – <hy geother al=

30



Use Logic

• 8e#uctive – -re ises – Inference – ConclusionStart (ith a ;re ise If all the ;re ises

are true then the conclusion ust hol#

• In#uctive – -re ises ;rovi#e evi#ence – ;en to #e.ate

31



In*Class "i e to<or) on &ssign ent• Brainstorm

together

• #sk me ,uestions• Inter iew e.perts

• 8on t ;rocrastinate• 8on t ;lagiarize• 8on t co;y your

class ates

T#/ M0 #D1I2

U ?&6E BEE<&, E8

bz dm mdl - lecture 4

Documents