Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
Chapter 1 End-of-Chapter Assignment Solutions
Multiple Choice Questions
1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to accomplish a
specific business task is called _.
a. business processes
b. business analysis
c. business procedure
d. business value
2. (LO 1.2) According to the information value chain, data combined with context is
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate results to the
decision maker?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
4. (LO 1.5) Which phase of the SOAR analytics model involves jfinding jthe jmost jappropriate jdata jneeded jto
jaddress j the jbusiness jquestion?
a. Specify jthe jquestion
b. j j j Obtain jthe jdata
c. Analyze jthe jdata
d. Report jthe jresults
5. (LO j1.5) jWhich jquestions jseek jinformation jabout jTesla’s jsales jin jthe jnext jquarter?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast
jwhat j will jhappen?
d. j j j What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
6. (LO j1.5) jWhich jquestions jseek jinformation jon jthe jrouting jof jproducts jfrom jQueretaro, jMexico jto
jChicago, j United jStates jin jthe jlast jquarter?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
1
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
7. (LO j1.5) jWhich jquestions jask jwhy jnet jincome jis jincreasing jwhen jrevenues jare jdecreasing,
jcounter jto j expectations?
a. What jhappened? jWhat jis jhappening?
b. j j j Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
8. (LO j1.5) jWhich jquestions jhelp jmanagers junderstand jhow jto jorganize jfuture jshipments jbased jon
jexpected j demand?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. j j j What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour
jperformance j based jon jpotential jconstraints?
9. (LO j1.5) jWhich jterm jrefers jto jthe jcombined jaccuracy, jvalidity, jand jconsistency jof jdata jstored jand jused
jover j time?
a. Data jintegrity
b. Data joverload
c. Data jvalue
d. Information jvalue
10. (LO j1.3) jA jspecialist jwho jknows jhow jto jwork jwith, jmanipulate, jand jstatistically jtest jdata jis ja
a. decision jmaker.
b. j j j data jscientist.
c. data janalyst.
d. decision jscientist.
11. (LO j1.4) jWhich jtype jof janalysts jpredicts jthe jamount jof jmoney jthat ja jcompany jwill jreceive jfrom jits
jcustomers jto j help jmanagement jevaluate jfuture jinvestments jbased jon jexpected jinvestment jperformance,
jsuch jas j j investments jin jequipment jor jemployee jtraining?
a. Marketing janalyst
b. Operations janalyst
c. Financial janalyst
d. j j j Accounting janalyst
12. (LO j1.4) jWhich jtype jof janalyst jaddresses jquestions jregarding jtax jand jauditing?
a. Marketing janalyst
b. Operations janalyst
c. Financial janalyst
d. j j j Accounting janalyst
13. (LO j1.5) jSuppose ja jcompany jhas jtimely jproduct jreviews jthat jare javailable jwhen jneeded, jbut jthe jreviews
jare j biased. jThese jproduct jreviews jare jwhich jtype jof jdata?
a. Reliable
b. j j j Relevant
c. Curated
d. Consistent
© jMcGraw jHill jLLC. jAll jrights jreserved. jNo jreproduction jor jdistribution jwithout jthe jprior jwritten jconsent jof jMcGraw jHill
jLLC.
2
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
14. (LO j1.6) jWhich jcommon jvisualization jtype jshows jtrends jin jvalues jover jtime?
a. Line jgraph
b. Scatterplot
c. Pie jchart
d. Bar jchart
15. (LO j1.6) jWhich jcommon jvisualization jtype jshows jthe jcomposition jof jvalues jover jtime?
a. Line jgraph
b. Scatterplot
c. Pie jchart
d. j j j Bar jchart
Discussion jQuestions
1. (LO j1.1) jGive jfive jexamples jof jbusiness jprocesses jat jTesla. j jHow jdo jthey jcreate jbusiness jvalue jfor jTesla
jand jits j shareholders?
SuggestedjSolution:
Answers jwill jvary,
1. Tesla jprocures jautomobile jparts jfrom jauto jsuppliers j– Because jof jTesla’s junique jstyling, jgetting jquality
parts jfrom jits jsuppliers jon ja jtimely jbasis jwill jsupport jits jmanufacturing jbusiness.
2. Tesla jmanufactures jbatteries jfor jits jelectric jvehicle jat jits jdesired jspecifications j– jThe jquantity jand
jquality j of jits jbatteries jare jof jcritical jimportance jto jTesla.
3. Accepting jand jprocessing jpreorders jfrom jits jcustomers j– jTesla jreceives jsome jindication jof jthe jdemand
jfor j each jof jits jproducts, jthat jhelps jwith jplanning.
4. Tesla jmarkets jits jproducts j– jTesla jworks jto jget jTesla jproducts jin jthe jfront jof jmind jfor jits jcustomers.
5. Tesla jcar jand jtruck jdesign j– jTesla jdesigns jits jautomobiles jin ja jway jthat jwill jappeal jto jits jcustomers
j(for j example, jCybertruck).
2. (LO j1.2) jExplain jthe jinformation jvalue jchain jby jsummarizing jhow jdata jare jtransformed jinto jknowledge
jinsights j for jdecision-making. jUse jthe jexample jof ja jbook jreview jon jAmazon jand jhow jit jmight jlead jAmazon
jto jdecide jhow j many jof jthose jbooks jto jstock jat jits jwarehouses.
SuggestedjSolution:
Amazon jallows jthose jwho jpurchase jbooks jand jother jproducts jat jits jwebsite jto jgive jproduct jreviews jand
jassign j product jratings. j The jproduct jreviews jmay jprovide jtext jwhich jtextual janalytics jcould juse jto
junderstand jthe j general jsentiment jabout jthe jspecific jbook. j The jproduct jrating jcould jalso jbe jused jto
junderstand jhow jwell jthe j book jis jliked jby jverified jbuyers. j Statistical jcorrelations jcould jbe jrun jamong
jproduct jreview jsentiment, jproduct j ratings jand jproduct jsales jto jhelp jforecast jdemand jfor jthe jproduct.
j This jwill jhelp jAmazon jdetermine jhow jmany j books jto jkeep jin jits jwarehouse jready jfor jdelivery.
This jis jan jexample jof jhow jdata jturns jinto jinformation, jknowledge jand jultimately jhelps jwith jdecision jmaking.
3. (LO j1.3) jExplain jthe jinformation jvalue jchain jby jsummarizing jhow jdata jare jtransformed jinto jknowledge
jinsights j for jdecision-making. jUse jthe jexample jof ja jbook jreview jof jthis jbook jon jAmazon jand jhow jit jmight
jhelp jthe j publisher, jMcGraw jHill, jdetermine jwhether jto jrevise jthis jbook jfor ja jnew, jupdated jedition jas jthe
jdiscipline jof j data janalytics jevolves.
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
3
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
Suggested Solution:
McGraw jHill jwill juse jmany jdeterminants jto jdetermine jhow jwell jeach jone jof jits jtextbooks jare jperforming.
j They’ll jlook jat joverall jsales jof jthe jbook, jcompared jto jcompetitors. j But jthey jmay jalso jsurvey jusers jto
jdetermine j how jwell jthe jbook jis jliked, jwhat jis jdeficient jin jthe jbook, jwhat jnew jtopics jshould jbe
jconsidered, jetc. j All jtold, jall j of jthe jdata jwill jbe jput jtogether, janalyzed, jknowledge jwill jbe jgained, jand ja
jdecision jwill jbe jmade.
4. (LO j1.3) jExplain jthe jdifference jbetween ja jdecision-maker, ja jdata jscientist, jand ja jbusiness janalyst. jWhat jis
jthe j role jof jeach?
SuggestedjSolution:
While jthere jare jnot jalways jdefinitive jdistinctions jbetween jthese jthree jpositions, jthe jdecision jmaker jneeds
j questions janswered jbefore jthey jcan jmake jdata-informed jdecisions. j The jdata jscientist jis jmost jfamiliar
jwith jthe j data, jas jthat jis jtheir jspecialty, jcollecting jand jmaintaining jdata jin jdatabases, jmanipulating,
jtransforming jand j analyzing jdata. j jThe jbusiness janalyst jgenerally junderstands jthe jbusiness jand jthe
jinformation jneeds jof jthe j decision jmaker, jbut jalso junderstands jthe jdata. j The jbusiness janalyst jcan jserve
jas ja jgo jbetween, jbetween jthe j decision jmaker jand jthe jdata jscientist, jall jworking jtogether jto jmake jdata-
informed jdecisions.
5. (LO1.4) jCompare jand jcontrast jmarketing janalytics jwith jaccounting janalytics. j How jare jthey jsimilar? jHow
jare j they jdifferent?
SuggestedjSolution:
Both jmarketing jand jaccounting janalytics jaddress jmanagement jquestions jusing jappropriate jdata jand janalytics.
j But jthey jalso jdiffer jfrom jeach jother. jFor jexample, jmarketing janalytics jare jused jto jaddress jthe jneeds jof jthe
j marketing jdepartment, jthe jbusiness jof jpromoting jand jselling jproducts jand jservices. j Marketing janalytics jis j
j often jinvolved jin jproviding jinsights jinto jcustomer jpreferences jand jtrends. j In jcontrast, jaccounting janalytics
juses j business janalytics jto jhelp jmeasure jaccounting jperformance jand jaddress jaccounting jquestions, jsuch
jas janalyzing j whether ja jcompany jcommitted jfraud jor jpredicting jfuture jsales jor jearnings jof ja jcompany.
6. (LO1.4) jCompare jand jcontrast jfinancial janalytics jwith joperations janalytics. j. j jHow jare jthey jsimilar? jHow
jare j they jdifferent?
SuggestedjSolution:
Both jfinancial janalytics jand joperations janalytics jaddress jmanagement jquestions jusing jappropriate jdata jand
j analytics. j But jthey jalso jdiffer jfrom jeach jother. j For jexample, jfinancial janalytics juses jbusiness janalytics jto
jhelp ja j company jmeasure jand jevaluate jits jfinancial jperformance, jfrom jpredicting jreceivables jcollection
jfrom jits j customers jto jhelping jmanagement jevaluate jfuture jinvestments jbased jon jexpected jinvestment
jperformance. j In j contrast, joperations janalytics juses jbusiness janalytics jto jmeasure jand jimprove jthe
jefficiency jand jeffectiveness jof j the jcompany’s joperations, jsince joperations jis jall jactions jneeded jto jrun jthe
jcompany jand jgenerate jincome.
7. (LO j1.5) jIdentify jthe jfour jsteps jin jthe jSOAR janalytics jmodel. jExplain jhow jmarketing janalysts jmight juse jthe
jSOAR j model jto jhelp jNetflix jbetter junderstand jits jcustomers.
4
Chapter 1 End-of-Chapter Assignment Solutions
Multiple Choice Questions
1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to accomplish a
specific business task is called _.
a. business processes
b. business analysis
c. business procedure
d. business value
2. (LO 1.2) According to the information value chain, data combined with context is
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate results to the
decision maker?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
4. (LO 1.5) Which phase of the SOAR analytics model involves jfinding jthe jmost jappropriate jdata jneeded jto
jaddress j the jbusiness jquestion?
a. Specify jthe jquestion
b. j j j Obtain jthe jdata
c. Analyze jthe jdata
d. Report jthe jresults
5. (LO j1.5) jWhich jquestions jseek jinformation jabout jTesla’s jsales jin jthe jnext jquarter?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast
jwhat j will jhappen?
d. j j j What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
6. (LO j1.5) jWhich jquestions jseek jinformation jon jthe jrouting jof jproducts jfrom jQueretaro, jMexico jto
jChicago, j United jStates jin jthe jlast jquarter?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
1
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
7. (LO j1.5) jWhich jquestions jask jwhy jnet jincome jis jincreasing jwhen jrevenues jare jdecreasing,
jcounter jto j expectations?
a. What jhappened? jWhat jis jhappening?
b. j j j Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour jperformance
jbased j on jpotential jconstraints?
8. (LO j1.5) jWhich jquestions jhelp jmanagers junderstand jhow jto jorganize jfuture jshipments jbased jon
jexpected j demand?
a. What jhappened? jWhat jis jhappening?
b. Why jdid jit jhappen? jWhat jare jthe jcauses jof jpast jresults?
c. Will jit jhappen jin jthe jfuture? jWhat jis jthe jprobability jsomething jwill jhappen? jCan jwe jforecast jwhat
jwill j happen?
d. j j j What jshould jwe jdo, jbased jon jwhat jwe jexpect jwill jhappen? jHow jdo jwe joptimize jour
jperformance j based jon jpotential jconstraints?
9. (LO j1.5) jWhich jterm jrefers jto jthe jcombined jaccuracy, jvalidity, jand jconsistency jof jdata jstored jand jused
jover j time?
a. Data jintegrity
b. Data joverload
c. Data jvalue
d. Information jvalue
10. (LO j1.3) jA jspecialist jwho jknows jhow jto jwork jwith, jmanipulate, jand jstatistically jtest jdata jis ja
a. decision jmaker.
b. j j j data jscientist.
c. data janalyst.
d. decision jscientist.
11. (LO j1.4) jWhich jtype jof janalysts jpredicts jthe jamount jof jmoney jthat ja jcompany jwill jreceive jfrom jits
jcustomers jto j help jmanagement jevaluate jfuture jinvestments jbased jon jexpected jinvestment jperformance,
jsuch jas j j investments jin jequipment jor jemployee jtraining?
a. Marketing janalyst
b. Operations janalyst
c. Financial janalyst
d. j j j Accounting janalyst
12. (LO j1.4) jWhich jtype jof janalyst jaddresses jquestions jregarding jtax jand jauditing?
a. Marketing janalyst
b. Operations janalyst
c. Financial janalyst
d. j j j Accounting janalyst
13. (LO j1.5) jSuppose ja jcompany jhas jtimely jproduct jreviews jthat jare javailable jwhen jneeded, jbut jthe jreviews
jare j biased. jThese jproduct jreviews jare jwhich jtype jof jdata?
a. Reliable
b. j j j Relevant
c. Curated
d. Consistent
© jMcGraw jHill jLLC. jAll jrights jreserved. jNo jreproduction jor jdistribution jwithout jthe jprior jwritten jconsent jof jMcGraw jHill
jLLC.
2
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
14. (LO j1.6) jWhich jcommon jvisualization jtype jshows jtrends jin jvalues jover jtime?
a. Line jgraph
b. Scatterplot
c. Pie jchart
d. Bar jchart
15. (LO j1.6) jWhich jcommon jvisualization jtype jshows jthe jcomposition jof jvalues jover jtime?
a. Line jgraph
b. Scatterplot
c. Pie jchart
d. j j j Bar jchart
Discussion jQuestions
1. (LO j1.1) jGive jfive jexamples jof jbusiness jprocesses jat jTesla. j jHow jdo jthey jcreate jbusiness jvalue jfor jTesla
jand jits j shareholders?
SuggestedjSolution:
Answers jwill jvary,
1. Tesla jprocures jautomobile jparts jfrom jauto jsuppliers j– Because jof jTesla’s junique jstyling, jgetting jquality
parts jfrom jits jsuppliers jon ja jtimely jbasis jwill jsupport jits jmanufacturing jbusiness.
2. Tesla jmanufactures jbatteries jfor jits jelectric jvehicle jat jits jdesired jspecifications j– jThe jquantity jand
jquality j of jits jbatteries jare jof jcritical jimportance jto jTesla.
3. Accepting jand jprocessing jpreorders jfrom jits jcustomers j– jTesla jreceives jsome jindication jof jthe jdemand
jfor j each jof jits jproducts, jthat jhelps jwith jplanning.
4. Tesla jmarkets jits jproducts j– jTesla jworks jto jget jTesla jproducts jin jthe jfront jof jmind jfor jits jcustomers.
5. Tesla jcar jand jtruck jdesign j– jTesla jdesigns jits jautomobiles jin ja jway jthat jwill jappeal jto jits jcustomers
j(for j example, jCybertruck).
2. (LO j1.2) jExplain jthe jinformation jvalue jchain jby jsummarizing jhow jdata jare jtransformed jinto jknowledge
jinsights j for jdecision-making. jUse jthe jexample jof ja jbook jreview jon jAmazon jand jhow jit jmight jlead jAmazon
jto jdecide jhow j many jof jthose jbooks jto jstock jat jits jwarehouses.
SuggestedjSolution:
Amazon jallows jthose jwho jpurchase jbooks jand jother jproducts jat jits jwebsite jto jgive jproduct jreviews jand
jassign j product jratings. j The jproduct jreviews jmay jprovide jtext jwhich jtextual janalytics jcould juse jto
junderstand jthe j general jsentiment jabout jthe jspecific jbook. j The jproduct jrating jcould jalso jbe jused jto
junderstand jhow jwell jthe j book jis jliked jby jverified jbuyers. j Statistical jcorrelations jcould jbe jrun jamong
jproduct jreview jsentiment, jproduct j ratings jand jproduct jsales jto jhelp jforecast jdemand jfor jthe jproduct.
j This jwill jhelp jAmazon jdetermine jhow jmany j books jto jkeep jin jits jwarehouse jready jfor jdelivery.
This jis jan jexample jof jhow jdata jturns jinto jinformation, jknowledge jand jultimately jhelps jwith jdecision jmaking.
3. (LO j1.3) jExplain jthe jinformation jvalue jchain jby jsummarizing jhow jdata jare jtransformed jinto jknowledge
jinsights j for jdecision-making. jUse jthe jexample jof ja jbook jreview jof jthis jbook jon jAmazon jand jhow jit jmight
jhelp jthe j publisher, jMcGraw jHill, jdetermine jwhether jto jrevise jthis jbook jfor ja jnew, jupdated jedition jas jthe
jdiscipline jof j data janalytics jevolves.
© McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.
3
, Chapter 01 – Specify the Question: Using Business Analytics to Address Business Questions
Suggested Solution:
McGraw jHill jwill juse jmany jdeterminants jto jdetermine jhow jwell jeach jone jof jits jtextbooks jare jperforming.
j They’ll jlook jat joverall jsales jof jthe jbook, jcompared jto jcompetitors. j But jthey jmay jalso jsurvey jusers jto
jdetermine j how jwell jthe jbook jis jliked, jwhat jis jdeficient jin jthe jbook, jwhat jnew jtopics jshould jbe
jconsidered, jetc. j All jtold, jall j of jthe jdata jwill jbe jput jtogether, janalyzed, jknowledge jwill jbe jgained, jand ja
jdecision jwill jbe jmade.
4. (LO j1.3) jExplain jthe jdifference jbetween ja jdecision-maker, ja jdata jscientist, jand ja jbusiness janalyst. jWhat jis
jthe j role jof jeach?
SuggestedjSolution:
While jthere jare jnot jalways jdefinitive jdistinctions jbetween jthese jthree jpositions, jthe jdecision jmaker jneeds
j questions janswered jbefore jthey jcan jmake jdata-informed jdecisions. j The jdata jscientist jis jmost jfamiliar
jwith jthe j data, jas jthat jis jtheir jspecialty, jcollecting jand jmaintaining jdata jin jdatabases, jmanipulating,
jtransforming jand j analyzing jdata. j jThe jbusiness janalyst jgenerally junderstands jthe jbusiness jand jthe
jinformation jneeds jof jthe j decision jmaker, jbut jalso junderstands jthe jdata. j The jbusiness janalyst jcan jserve
jas ja jgo jbetween, jbetween jthe j decision jmaker jand jthe jdata jscientist, jall jworking jtogether jto jmake jdata-
informed jdecisions.
5. (LO1.4) jCompare jand jcontrast jmarketing janalytics jwith jaccounting janalytics. j How jare jthey jsimilar? jHow
jare j they jdifferent?
SuggestedjSolution:
Both jmarketing jand jaccounting janalytics jaddress jmanagement jquestions jusing jappropriate jdata jand janalytics.
j But jthey jalso jdiffer jfrom jeach jother. jFor jexample, jmarketing janalytics jare jused jto jaddress jthe jneeds jof jthe
j marketing jdepartment, jthe jbusiness jof jpromoting jand jselling jproducts jand jservices. j Marketing janalytics jis j
j often jinvolved jin jproviding jinsights jinto jcustomer jpreferences jand jtrends. j In jcontrast, jaccounting janalytics
juses j business janalytics jto jhelp jmeasure jaccounting jperformance jand jaddress jaccounting jquestions, jsuch
jas janalyzing j whether ja jcompany jcommitted jfraud jor jpredicting jfuture jsales jor jearnings jof ja jcompany.
6. (LO1.4) jCompare jand jcontrast jfinancial janalytics jwith joperations janalytics. j. j jHow jare jthey jsimilar? jHow
jare j they jdifferent?
SuggestedjSolution:
Both jfinancial janalytics jand joperations janalytics jaddress jmanagement jquestions jusing jappropriate jdata jand
j analytics. j But jthey jalso jdiffer jfrom jeach jother. j For jexample, jfinancial janalytics juses jbusiness janalytics jto
jhelp ja j company jmeasure jand jevaluate jits jfinancial jperformance, jfrom jpredicting jreceivables jcollection
jfrom jits j customers jto jhelping jmanagement jevaluate jfuture jinvestments jbased jon jexpected jinvestment
jperformance. j In j contrast, joperations janalytics juses jbusiness janalytics jto jmeasure jand jimprove jthe
jefficiency jand jeffectiveness jof j the jcompany’s joperations, jsince joperations jis jall jactions jneeded jto jrun jthe
jcompany jand jgenerate jincome.
7. (LO j1.5) jIdentify jthe jfour jsteps jin jthe jSOAR janalytics jmodel. jExplain jhow jmarketing janalysts jmight juse jthe
jSOAR j model jto jhelp jNetflix jbetter junderstand jits jcustomers.
4
