SOLUTION MANUAL FOR
3 3
QUANTITATIVE 3ANALYSIS3FOR3MANAGEMENT,314TH3EDITION3RENDE
R
CHAPTER31-15
CHAPTER31
Introduction to Quantitative Analysis
3 3 3
TEACHING3SUGGESTIONS
Teaching3Suggestion31.1:3Importance3of3Qualitative3Factors.
Section31.13gives3students3an3overview3of3quantitative3analysis.3In3this3section,3a3number3of3qua
litative3factors,3including3federal3legislation3and3new3technology,3are3discussed.3Students3can3be
3asked3to3discuss3other3qualitative 3factors3that3could3have3an3impact 3on3quantitative 3analysis.3W
aiting3lines3and3project3planning3can3be3used3as3examples.
Teaching3Suggestion31.2:3Discussing3Other3Quantitative3Analysis3Problems.
Section31.23covers3an3application3of3the3quantitative3analysis3approach.3Students3can3be3asked3t
o3describe3other3problems3or3areas3that3could3benefit3from3quantitative3analysis.
Teaching3Suggestion31.3:3Discussing3Conflicting3Viewpoints.
Possible3problems3in3the3QA3approach3are3presented3in3this3chapter.3A3discussion3of3conflicting
3viewpoints3within3the3organization3can3help3students3understand3this3problem.3For3example,3ho
w3many3people3should3staff3a3registration3desk3at3a3university?3Students3will3want3more3staff3to
3reduce 3waiting3time,3while 3university3administrators3will3want 3less3staff3to3save 3money.3A3disc
ussion3of3these3types3of3conflicting3viewpoints3will3help3students3understand3some3of3the3proble
ms3of3using3quantitative3analysis.
Teaching3Suggestion31.4:3Difficulty3of3Getting3Input3Data.
A3major3problem3in3quantitative3analysis3is3getting3proper3input3data.3Students3can3be3asked3to3
explain3how3they3would3get3the3information3they3need3to3determine3inventory3ordering3or3carryi
ng3costs.3Role-
playing3with3students3assuming3the3parts3of3the3analyst3who3needs3inventory3costs3and3the3instr
uctor3playing3the3part3of3a3veteran3inventory3manager3can3be3fun3and3interesting.3Students3quick
ly3learn3that3getting3good3data3can3be3the3most3difficult3part3of3using3quantitative3analysis.
Teaching3Suggestion31.5:3Dealing3with3Resistance3to3Change.
11-1
Copyright3©320243Pearson3Education,3Inc.
,Resistance3to3change3is3discussed3in3this3chapter.3Students3can3be3asked3to3explain3how3they3wo
uld3introduce3a3new3system3or3change3within3the3organization.3People3resisting3new3approaches3
can3be3a3major3stumbling3block3to3the3successful3implementation3of3quantitative3analysis.3Stude
nts3can3be3asked3why3some3people3may3be3afraid3of3a3new3inventory3control3or3forecasting3syst
em.
SOLUTIONS3TO3DISCUSSION3QUESTIONS3AND3PROBLEMS
1-
1.3Quantitative3analysis3involves3the3use3of3mathematical3equations3or3relationships3in3analyzing
3a3particular3problem.3In3most3cases,3the 3results3of3quantitative 3analysis3will3be3one3or3more3nu
mbers3that3can3be3used3by3managers3and3decision3makers3in3making3better3decisions.3Calculatin
g3rates3of3return,3financial3ratios3from3a3balance3sheet3and3profit3and3loss3statement,3determinin
g3the3number3of3units3that3must3be3produced3in3order3to3break3even,3and3many3similar3technique
s3are3examples3of3quantitative3analysis.3Qualitative3analysis3involves3the3investigation3of3factors
3in3a3decision-
making3problem3that3cannot3be3quantified3or3stated3in3mathematical3terms.3The3state3of3the3econ
omy,3current3or3pending3legislation,3perceptions3about3a3potential3client,3and3similar3situations3r
eveal3the3use3of3qualitative3analysis.3In3most3decision-
making3problems,3both3quantitative3and3qualitative3analysis3are3used.3In3this3book,3however,3we
3emphasize 3the3techniques3and3approaches3of3quantitative 3analysis.
1-
2.3Quantitative3analysis3is3the3scientific3approach3to3managerial3decision3making.3This3type3of3a
nalysis3is3a3logical3and3rational3approach3to3making3decisions.3Emotions,3guesswork,3and3whim3
are3not3part3of3the3quantitative3analysis3approach.3A3number3of3organizations3support3the3use3of3
the3scientific3approach:3the3Institute3for3Operation3Research3and3Management3Science3(INFOR
MS),3Decision3Sciences3Institute,3and3Academy3of3Management.
1-
3.3The3three3categories3of3business3analytics3are3descriptive,3predictive,3and3prescriptive.3Descri
ptive3analytics3provides3an3indication3of3how3things3were3performed3in3the3past.3Predictive3anal
ytics3uses3past3data3to3forecast3what3will3happen3in3the3future.3Prescriptive3analytics3uses3optimi
zation3and3other3models3to3present3better3ways3for3a3company3to3operate3to3reach3goals3and3obje
ctives.
1-4.3Quantitative3analysis3is3a3step-by-
step3process3that3allows3decision3makers3to3investigate3problems3using3quantitative3techniques.3
The3steps3of3the3quantitative3analysis3process3include3defining3the3problem,3developing3a3model
,3acquiring3input3data,3developing3a3solution,3testing3 the3solution,3analyzing3the3results,3and3imp
lementing3the3results.3In3every3case,3the3analysis3begins3with3defining3the3problem.3The3proble
m3could3be3too3many3stockouts,3too3many3bad3 debts,3or3determining3the3products3to3produce3th
at3will3result3in3the3maximum3profit3for3the3organization.3After3the3problems3have3been3defined,
3the3next3step3is3to3develop3one3or3more 3models.3These 3models3could3be3inventory3control 3mode
ls,3models3that3describe3the3debt3situation3in3the3organization,3and3so3on.3Once3the3models3have3
been3developed,3the3next3step3is3to3acquire3input3data.3In3the3inventory3problem,3for3example,3su
ch3factors3as3the3annual3demand,3the3ordering3cost,3and3the3carrying3cost3would3be3input3data3th
at3are3used3by3the3model3developed3in3the3preceding3step.3In3determining3the3products3to3produc
11-2
Copyright3©320243Pearson3Education,3Inc.
,e3in3order3to3maximize3profits,3the3input3data3could3be3such3things3as3the3profitability3for3all3the
3different 3products,3the3amount 3of3time3 that3is3available 3at3the3various3production3departments3t
hat3produce3the3products,3and3the3amount3of3time3it3takes3for3each3product3to3be3produced3in3ea
ch3production3department.3The3next3step3is3developing3 the3 solution.3 This3 requires3 manipulation
3 of3 the3 model3 in3 order3 to3 determine 3 the3 best
11-3
Copyright3©320243Pearson3Education,3Inc.
, solution.3Next,3the3results3are3tested,3analyzed,3and3implemented.3In3the3inventory3control3probl
em,3this3might3result3in3determining3and3implementing3a3policy3to3order3a3certain3amount3of3inv
entory3at3specified3intervals.3For3the3problem3of3determining3the3best3products3to3produce,3this3
might3mean3testing,3analyzing,3and3implementing3a3decision3to3produce3a3certain3quantity3of3giv
en3products.
1-
5.3Although3the3formal3study3of3quantitative3analysis3and3the3refinement3of3the3tools3and3techni
ques3of3the3scientific3method3have3occurred3only3in3the3recent3past,3quantitative3approaches3to3d
ecision3making3have3been3in3existence3since3the3beginning3of3time.3In3the3early31900s,3Frederic
k3W.3Taylor3developed3the3principles3of3the3scientific3approach.3During3World3War3II,3quantitat
ive3analysis3was3intensified3and3used3by3the3military.3Because3of3the3success3of3these3technique
s3during3World3War3II,3interest3continued3after3the3war.
1-
6.3Model3types3include3the3scale3model,3physical3model,3and3schematic3model3(which3is3a3pictur
e3or3drawing3of3reality).3In3this3book,3mathematical3models3are3used3to3describe3mathematical3r
elationships3in3solving3quantitative3problems.
In3this3question,3the3student3is3asked3to3develop3two3mathematical3models.3The3student3mig
ht3develop3a3number3of3models3that3relate3to3finance,3marketing,3accounting,3statistics,3or3other3
fields.3The3purpose3of3this3part3of3the3question3is3to3have3the3student3develop3a3mathematical3rel
ationship3between3variables3with3which3the3student3is3familiar.
1-
7.3 Input3data3can3come3from3company3reports3and3documents,3interviews3with3employees3and3o
ther3personnel,3direct3measurement,3and3sampling3procedures.3For3many3problems,3a3number3of3
different3sources3are3required3to3obtain3data,3and3in3some3cases3it3is3necessary3to3obtain3the3sam
e3data3from3different3sources3in3order3to3check3the3accuracy3and3consistency3of3the3input3data.3I
f3 the3input3data3are3not3accurate,3the3results3can3be3misleading3and3very3costly3to3the3organizati
on.3This3concept3is3called3―garbage3in,3garbage3out.‖
1-
8.3 Implementation3is3the3process3of3taking3the3solution3and3incorporating3it3into3the3company3 o
r3organization.3This3is3the3final3step3in3the3quantitative3analysis3approach,3and3if3a3good3job3is3n
ot3done3with3implementation,3all3of3the3effort3expended3on3the3previous3steps3can3be3wasted.
1-
9.3 Sensitivity3analysis3and3post3optimality3analysis3allow3the3decision3maker3to3determine3how3t
he3final3solution3to3the3problem3will3change3when3the3input3data3or3the3model3change.3This3type
3of3analysis3is3very3important 3when3the3input3data3or3model 3has3not3been3specified3properly.3A3s
ensitive3solution3is3one3in3which3the3results3of3the3solution3to3the3problem3will3change3 drasticall
y3or3by3a3large3amount3with3small3changes3in3the3data3or3in3the3model.3When3the3model3is3not3s
ensitive,3the3results3or3solutions3to3the3model3will3not3change3significantly3with3changes3in3the3i
nput3data3or3in3the3model.3Models3that3are3very3sensitive3require3that3the3input3data3and3the3mod
el3itself3be3thoroughly3tested3to3make3sure3that3both3are3very3accurate3and3consistent3with3the3pr
oblem3statement.
1-
10.3 There3are3a3large3number3of3quantitative3terms3that3may3not3be3understood3by3managers.3Ex
amples3include3PERT,3CPM,3simulation,3the3Monte3Carlo3method,3mathematical3programming,3
11-4
Copyright3©320243Pearson3Education,3Inc.
3 3
QUANTITATIVE 3ANALYSIS3FOR3MANAGEMENT,314TH3EDITION3RENDE
R
CHAPTER31-15
CHAPTER31
Introduction to Quantitative Analysis
3 3 3
TEACHING3SUGGESTIONS
Teaching3Suggestion31.1:3Importance3of3Qualitative3Factors.
Section31.13gives3students3an3overview3of3quantitative3analysis.3In3this3section,3a3number3of3qua
litative3factors,3including3federal3legislation3and3new3technology,3are3discussed.3Students3can3be
3asked3to3discuss3other3qualitative 3factors3that3could3have3an3impact 3on3quantitative 3analysis.3W
aiting3lines3and3project3planning3can3be3used3as3examples.
Teaching3Suggestion31.2:3Discussing3Other3Quantitative3Analysis3Problems.
Section31.23covers3an3application3of3the3quantitative3analysis3approach.3Students3can3be3asked3t
o3describe3other3problems3or3areas3that3could3benefit3from3quantitative3analysis.
Teaching3Suggestion31.3:3Discussing3Conflicting3Viewpoints.
Possible3problems3in3the3QA3approach3are3presented3in3this3chapter.3A3discussion3of3conflicting
3viewpoints3within3the3organization3can3help3students3understand3this3problem.3For3example,3ho
w3many3people3should3staff3a3registration3desk3at3a3university?3Students3will3want3more3staff3to
3reduce 3waiting3time,3while 3university3administrators3will3want 3less3staff3to3save 3money.3A3disc
ussion3of3these3types3of3conflicting3viewpoints3will3help3students3understand3some3of3the3proble
ms3of3using3quantitative3analysis.
Teaching3Suggestion31.4:3Difficulty3of3Getting3Input3Data.
A3major3problem3in3quantitative3analysis3is3getting3proper3input3data.3Students3can3be3asked3to3
explain3how3they3would3get3the3information3they3need3to3determine3inventory3ordering3or3carryi
ng3costs.3Role-
playing3with3students3assuming3the3parts3of3the3analyst3who3needs3inventory3costs3and3the3instr
uctor3playing3the3part3of3a3veteran3inventory3manager3can3be3fun3and3interesting.3Students3quick
ly3learn3that3getting3good3data3can3be3the3most3difficult3part3of3using3quantitative3analysis.
Teaching3Suggestion31.5:3Dealing3with3Resistance3to3Change.
11-1
Copyright3©320243Pearson3Education,3Inc.
,Resistance3to3change3is3discussed3in3this3chapter.3Students3can3be3asked3to3explain3how3they3wo
uld3introduce3a3new3system3or3change3within3the3organization.3People3resisting3new3approaches3
can3be3a3major3stumbling3block3to3the3successful3implementation3of3quantitative3analysis.3Stude
nts3can3be3asked3why3some3people3may3be3afraid3of3a3new3inventory3control3or3forecasting3syst
em.
SOLUTIONS3TO3DISCUSSION3QUESTIONS3AND3PROBLEMS
1-
1.3Quantitative3analysis3involves3the3use3of3mathematical3equations3or3relationships3in3analyzing
3a3particular3problem.3In3most3cases,3the 3results3of3quantitative 3analysis3will3be3one3or3more3nu
mbers3that3can3be3used3by3managers3and3decision3makers3in3making3better3decisions.3Calculatin
g3rates3of3return,3financial3ratios3from3a3balance3sheet3and3profit3and3loss3statement,3determinin
g3the3number3of3units3that3must3be3produced3in3order3to3break3even,3and3many3similar3technique
s3are3examples3of3quantitative3analysis.3Qualitative3analysis3involves3the3investigation3of3factors
3in3a3decision-
making3problem3that3cannot3be3quantified3or3stated3in3mathematical3terms.3The3state3of3the3econ
omy,3current3or3pending3legislation,3perceptions3about3a3potential3client,3and3similar3situations3r
eveal3the3use3of3qualitative3analysis.3In3most3decision-
making3problems,3both3quantitative3and3qualitative3analysis3are3used.3In3this3book,3however,3we
3emphasize 3the3techniques3and3approaches3of3quantitative 3analysis.
1-
2.3Quantitative3analysis3is3the3scientific3approach3to3managerial3decision3making.3This3type3of3a
nalysis3is3a3logical3and3rational3approach3to3making3decisions.3Emotions,3guesswork,3and3whim3
are3not3part3of3the3quantitative3analysis3approach.3A3number3of3organizations3support3the3use3of3
the3scientific3approach:3the3Institute3for3Operation3Research3and3Management3Science3(INFOR
MS),3Decision3Sciences3Institute,3and3Academy3of3Management.
1-
3.3The3three3categories3of3business3analytics3are3descriptive,3predictive,3and3prescriptive.3Descri
ptive3analytics3provides3an3indication3of3how3things3were3performed3in3the3past.3Predictive3anal
ytics3uses3past3data3to3forecast3what3will3happen3in3the3future.3Prescriptive3analytics3uses3optimi
zation3and3other3models3to3present3better3ways3for3a3company3to3operate3to3reach3goals3and3obje
ctives.
1-4.3Quantitative3analysis3is3a3step-by-
step3process3that3allows3decision3makers3to3investigate3problems3using3quantitative3techniques.3
The3steps3of3the3quantitative3analysis3process3include3defining3the3problem,3developing3a3model
,3acquiring3input3data,3developing3a3solution,3testing3 the3solution,3analyzing3the3results,3and3imp
lementing3the3results.3In3every3case,3the3analysis3begins3with3defining3the3problem.3The3proble
m3could3be3too3many3stockouts,3too3many3bad3 debts,3or3determining3the3products3to3produce3th
at3will3result3in3the3maximum3profit3for3the3organization.3After3the3problems3have3been3defined,
3the3next3step3is3to3develop3one3or3more 3models.3These 3models3could3be3inventory3control 3mode
ls,3models3that3describe3the3debt3situation3in3the3organization,3and3so3on.3Once3the3models3have3
been3developed,3the3next3step3is3to3acquire3input3data.3In3the3inventory3problem,3for3example,3su
ch3factors3as3the3annual3demand,3the3ordering3cost,3and3the3carrying3cost3would3be3input3data3th
at3are3used3by3the3model3developed3in3the3preceding3step.3In3determining3the3products3to3produc
11-2
Copyright3©320243Pearson3Education,3Inc.
,e3in3order3to3maximize3profits,3the3input3data3could3be3such3things3as3the3profitability3for3all3the
3different 3products,3the3amount 3of3time3 that3is3available 3at3the3various3production3departments3t
hat3produce3the3products,3and3the3amount3of3time3it3takes3for3each3product3to3be3produced3in3ea
ch3production3department.3The3next3step3is3developing3 the3 solution.3 This3 requires3 manipulation
3 of3 the3 model3 in3 order3 to3 determine 3 the3 best
11-3
Copyright3©320243Pearson3Education,3Inc.
, solution.3Next,3the3results3are3tested,3analyzed,3and3implemented.3In3the3inventory3control3probl
em,3this3might3result3in3determining3and3implementing3a3policy3to3order3a3certain3amount3of3inv
entory3at3specified3intervals.3For3the3problem3of3determining3the3best3products3to3produce,3this3
might3mean3testing,3analyzing,3and3implementing3a3decision3to3produce3a3certain3quantity3of3giv
en3products.
1-
5.3Although3the3formal3study3of3quantitative3analysis3and3the3refinement3of3the3tools3and3techni
ques3of3the3scientific3method3have3occurred3only3in3the3recent3past,3quantitative3approaches3to3d
ecision3making3have3been3in3existence3since3the3beginning3of3time.3In3the3early31900s,3Frederic
k3W.3Taylor3developed3the3principles3of3the3scientific3approach.3During3World3War3II,3quantitat
ive3analysis3was3intensified3and3used3by3the3military.3Because3of3the3success3of3these3technique
s3during3World3War3II,3interest3continued3after3the3war.
1-
6.3Model3types3include3the3scale3model,3physical3model,3and3schematic3model3(which3is3a3pictur
e3or3drawing3of3reality).3In3this3book,3mathematical3models3are3used3to3describe3mathematical3r
elationships3in3solving3quantitative3problems.
In3this3question,3the3student3is3asked3to3develop3two3mathematical3models.3The3student3mig
ht3develop3a3number3of3models3that3relate3to3finance,3marketing,3accounting,3statistics,3or3other3
fields.3The3purpose3of3this3part3of3the3question3is3to3have3the3student3develop3a3mathematical3rel
ationship3between3variables3with3which3the3student3is3familiar.
1-
7.3 Input3data3can3come3from3company3reports3and3documents,3interviews3with3employees3and3o
ther3personnel,3direct3measurement,3and3sampling3procedures.3For3many3problems,3a3number3of3
different3sources3are3required3to3obtain3data,3and3in3some3cases3it3is3necessary3to3obtain3the3sam
e3data3from3different3sources3in3order3to3check3the3accuracy3and3consistency3of3the3input3data.3I
f3 the3input3data3are3not3accurate,3the3results3can3be3misleading3and3very3costly3to3the3organizati
on.3This3concept3is3called3―garbage3in,3garbage3out.‖
1-
8.3 Implementation3is3the3process3of3taking3the3solution3and3incorporating3it3into3the3company3 o
r3organization.3This3is3the3final3step3in3the3quantitative3analysis3approach,3and3if3a3good3job3is3n
ot3done3with3implementation,3all3of3the3effort3expended3on3the3previous3steps3can3be3wasted.
1-
9.3 Sensitivity3analysis3and3post3optimality3analysis3allow3the3decision3maker3to3determine3how3t
he3final3solution3to3the3problem3will3change3when3the3input3data3or3the3model3change.3This3type
3of3analysis3is3very3important 3when3the3input3data3or3model 3has3not3been3specified3properly.3A3s
ensitive3solution3is3one3in3which3the3results3of3the3solution3to3the3problem3will3change3 drasticall
y3or3by3a3large3amount3with3small3changes3in3the3data3or3in3the3model.3When3the3model3is3not3s
ensitive,3the3results3or3solutions3to3the3model3will3not3change3significantly3with3changes3in3the3i
nput3data3or3in3the3model.3Models3that3are3very3sensitive3require3that3the3input3data3and3the3mod
el3itself3be3thoroughly3tested3to3make3sure3that3both3are3very3accurate3and3consistent3with3the3pr
oblem3statement.
1-
10.3 There3are3a3large3number3of3quantitative3terms3that3may3not3be3understood3by3managers.3Ex
amples3include3PERT,3CPM,3simulation,3the3Monte3Carlo3method,3mathematical3programming,3
11-4
Copyright3©320243Pearson3Education,3Inc.
