Research on using ANP to establish a performance assessment model for business intelligence ...

12 Pages·2008·0.27 MB·English

ExpertSystemswithApplications36(2009)4135–4146
ContentslistsavailableatScienceDirect
Expert Systems with Applications
journal homepage: www.elsevier.com/locate/eswa
Research on using ANP to establish a performance assessment model
for business intelligence systems
Yu-Hsin Lina,*, Kune-Muh Tsaib, Wei-Jung Shiangc, Tsai-Chi Kuoa, Chih-Hung Tsaid
aDepartmentofIndustrialEngineeringandManagement,Ming-HsinUniversityofScienceandTechnology,1HsinhsinRoad,Hsinfong30401,Hsin-Chu,Taiwan,ROC
bDepartmentofLogisticsManagement,NationalKaohsiungFirstUniversityofScienceandTechnology,No.2,JhuoyueRoad,NazihDistrict,Kaohsiung,Taiwan,ROC
cDepartmentofIndustrialEngineering,ChungYuanChristianUniversity200,ChungPeiRoad,ChungLi32023,Taiwan,ROC
dDepartmentofIndustrialEngineeringandManagement,Ta-HwaInstituteofTechnology,1Ta-HwaRoad,Chung-Lin,Hsin-Chu,Taiwan,ROC
a r t i c l e i n f o a b s t r a c t
Keywords: Inordertocompeteintherigorousenvironment,theelectronizationhasenabledbusinesstodeploybusi-
Businessintelligence nessintelligence(BI)systemsforthepurposeofdecision-making.However,toavoidtheineffectiveexpe-
Analyticnetworkprocess riencesduringthedeployment,itisimportanttoclarifytheimpactfactorsofaBIsystemandfindouta
Performanceindices
suitableassessmentmethodtoevaluatetheperformanceofBIsystems.Inthispaper,ananalyticnetwork
process(ANP)basedassessmentmodelwasconstructedtoassesstheeffectivenessofBIsystems.Fur-
thermore,anexpertquestionnairewasusedtofilteroutusefulperformancematrices,usedasthesub-
criteriaoftheANPmodel.Finally,arealcasewasanalyzedusingtheconstructedANP-basedeffectiveness
assessmentmodelforBusinessIntelligencesystems.Theresultsindicatethatthemostcriticalfactors
thatimpacttheeffectivenessofaBIsystemare:outputinformationaccuracy,conformitytotherequire-
ments,andsupportoforganizationalefficiency.UtilizingthismodeltoassesstheBIperformanceofthe
studiedcase,itrevealsthat24%improvementineffectivenesshasbeenreached,whichconsistswiththe
perceptionofthemanagementlevel.Therefore,thiseffectivenessassessmentmodelcanbeusedtoeval-
uatetheperformancesofaBIsystem.Itcanalsoprovideperformanceindicesandimprovementdirec-
tions for BI users and vendors, respectively, for the total succession in system effectiveness and
satisfaction.
(cid:2)2009-ElsevierLtd.Allrightsreserved.
1.Introduction accuracy and in real-time, in order to expedite the speed of pro-
cessing and decision-making. Existing electronization software
Traditional enterprises may normally face issues such as the packagecanprovideasetofcompletesolutionsfortheoperation
overflow of data, the lack of information, the lack of knowledge and management processes of enterprises. However, the effects
and insufficiency of reports. Therefore, in order to make prompt oftheimplementationofelectronizationtoolsvarythattheprob-
decisionwithintheshortestperiodoftimepossibletokeeppace abilityoffailureishigherthanthatofthesuccess(Ward,Heming-
with the situation, high levels of management commonly make way, & Daniel, 2005). Therefore, defining the performance of
decisionsbasedontheirexperiences,leadingtotheever-increas- information tool and laying down related assessment criteria is
ingriskofdecisionfailurewhileloweringthevalueofthedecision an important issue that has to be tackled for the deployment of
itself.Asworldwidecompetitionismaturating,pastdecision-mak- electronization.
ingmodescannolongersatisfytherequirementsofenterprisesfor Businessintelligence(BI)isthetoolusedbyenterprisestocol-
decisionefficiencyandbenefits;enterprisesmustmakegooduse lect, manage and analyze structural and non-structural data and
ofelectronictoolstoquicklyextractusefulinformationfromhuge information by takingadvantage ofmodern information technol-
volumeofdatabyprovidingtheskillsoffastdecision-making(Ra- ogy (IT). It utilizes a substantial amount of collected data during
kar&Jovan,2004).Thewaytopromotetheelectronizationsolu- thedailyoperationalprocesses,andtransformsthedataintoinfor-
tions from the operational levelto the decision making levelis a mationandknowledgetoavoidthesuppositionandignoranceof
topic enterprises cannot avoid in the face of the next wave of theenterprises(Wang,2005).Underthespeed-orientedoperation
electronization.Theinformationsystemappliedwithintheenter- mode,inordertoimprovemanagementeffectsandperformance,
prisesshouldbeabletodemonstratethedataorinformationwith BIwillsurelybecomethetoolenterpriseswouldliketoactivelyde-
ployaswellasthesolutionthatcanbringenterprisescompetitive
* Correspondingauthor.Tel.:[phone];fax:[phone]x3212. edge. However, current BI application is still at its fledging stage
E-mailaddress:[email protected](Y.-H.Lin). and most of the enterprises fall short of sufficient understanding
4136
towards BI (Wang, 2005); currently, research on conducting per- nessstatus,salesanalysis,customerdemand,productpreference,
formanceevaluationfortheimplementationofBIsystemisscarce, etc.isprovidedforenterprisesthroughlargedatabasesystemanal-
not to mention the analysis of on-line performance. Beside that, ysisaswellasmathematical,statistical,artificialintelligence,data
managersusuallyhavetomeasurealltheprosandconstoachieve mining and on-line analysis processing (OLAP) (Berson & Smith,
abalanceinassessingtheperformancesofBI/ITsystems.Different 1997;Thomsen,2002).EckersonWayne(2005)heldthatBImust
endusersandITpeopleadoptdifferentperformancemeasurement beabletoprovidethefollowingtools:productionreportingtools,
criteria.Therefore,itisasignificantissuetoimplementacross-the- end-user query and reporting tools, on-line analysis processing,
boardconsiderationstoincorporatedifferentviewpointsandper- dashboard/scorecardtools,dataminingtools,planningandmodel-
spectivesfrommanifoldexpertsinBIdevelopmentandusageinto ingtools.
thechoiceforassessingBIperformanceeffectiveness. BIisnotonlyatoolreflectingissues,butalsothemanagement
Inordertolowerthefailureriskafterimplementation,itisnec- of transferring internal messages in the enterprise environment
essarytoconductin-depthdiscussionfortheaforementionedissue. (EckersonWayne,2005).Therefore,apartfromsubstantialITsup-
Therefore,thisresearchstartsbyanalyzingBIbenefits,takesadvan- port, sound and proper planning abilities are needed when con-
tageofanalyticnetworkprocess(ANP)todiscussBIeffectiveness structing BI working environment, for example, ensuring the
andrelatedperformanceassessmentindications.Theresultsthus delivery and implementation of BI projects; ability of acquiring
provideenterprisesthatareinterestedindeployingBIsystemswith standardized data elements and changing process to ensure the
a consistent and effective assessment model for future BI imple- qualityofdataacquired,integratingallstrategicobjectiveswithin
mentationwhileservingasadirectionoffutureimprovementand the organization, and designing strategic map and transmitting
enhancementforBIsoftwaresuppliersandconsultingcompanies. important corporate value. Therefore, BI covers a wide range of
The remainder of this paper is organized as follows. Section2 tools and broad scope, and among the commonly mentioned
presents the related studies regarding to this research. Then, the important applications are data warehouse, data mining, OLAP,
research theory and method is presented in Section 3. Section 4 decision support system (DSS), balance scorecard (BSC), etc. All
demonstrates the proposed architecture for assessing the perfor- inall,thepurposeofBIistoprovideuserswiththebestpossible
mance of BI systems. An empirical research and related analysis assistanceintheprocessofdecision-making.Apartfromdelivering
is illustrated in Section 5. Then a case study on a global supplier therightinformationtorightpersonduringtherighttime(Back,
of computer peripherals is described in Section 6, and the sum- 2002; Eckerson Wayne, 2005), at the BI planning, implementing
maryandconclusionsaredrawnfinally. and go-live stages, enterprise operation contents and business
objectives must be understood in order to properly plan related
performance measurement indices and ensure the correctness
2.Informationsystems andvalidityoftheinformationprovidedbyBI.
Withthedemandsforinformationtechnology,applicationsoft- 2.2.Performancemeasurementindicesofinformationsystem
ware and enterprise information tactics constantly are enhanced
and expanded. The deployment of SCM, ERP, CRM systems, etc. Effectivelyassessingtheefficiencyofaninformationsystemis
hasbecomemature,andthegrowthofbusinessintelligenceinfor- the key element in the successful implementation of the system.
mationsystemwillbecomeanewdirectionforenterprises’electr- Assessing the performances of an information system means if
onizationconstruction(Chung,Lee,&Pearn,2005). the information system can be accepted by users, and if users’
work-related needs can be met and the objective at the initial
2.1.Businessintelligence implementationcanbeachieved.Astohowtoassesstheefficiency
ofinformationsystem,roughlyitcanbeclassifiedintotheassess-
Startingfromtheuseofinitialdatastoragedevices,enterprises ment of system satisfaction and the assessment of effectiveness.
have continued innovating and creating new system modes, in a Among the assessments of system satisfaction are contents cor-
pursuit of higher operation efficiency. After the development of rectness (Doll & Torzadeh, 1988; Ives, Olson, & Baroudi, 1983),
relational database, the development of business intelligence is resilience of the format (Doll & Torzadeh, 1988), easiness of the
then underway. Currently, there are multiple software suppliers operation(Doll&Torzadeh,1988;Tan&Lo,1990),real-timenat-
and specialty consulting companies conducting even more logic ure (Doll & Torzadeh, 1988), integrity of the output (Doll & Tor-
planning and enhancement for the function and applicability of zadeh, 1988), credibility of the output (Ives et al., 1983),
BIsystems,e.g.toolsassistingenterprisesindecision-makingsuch integrationandsafetyofthesystem(Tan&Lo,1990).Wildemann
asdatawarehouseandreal-timeanalysis.Hence,commerciallogic (1987)indicatedthatthesuccessoftheinformationsystemshould
thinkingisstillbeinginnovatedanddevelopedandthroughsuch beconsideredfrombothaspectsofthesuccessofprojectmanage-
processes, systematic enterprise operation mode is expected to mentandtheefficiencyofsoftwareexecutionatthetimeofsystem
becreatedtoenhancethecompetitiveedgeofenterprises. implementation.Ifabusinessintelligencesystemcanbesuccess-
Theapplicationofbusinessintelligenceistheprocessthrough fullyimplemented,itcanplayitsdueroleinfouraspects,namely,
whichenterprisestakeadvantagesofmoderninformationtechnol- assistinginunderstandingbusinessstatus,measuringorganization
ogy to collect, manage and analyze structural or non-structural performance, improving stakeholder relationship, and creating
data.Inorderwords,throughtheextraction,integrationandana- profitableopportunities(Wang,2005).
lysisofdata,technologyandcommercialprocessingproceduresin To prevent inefficiency of an information system after the
thedecision-makingaresupported(Wang,2005).Problemsanda introduction from appearing again, assessing the effectiveness
hugeamountofdataofenterprisesareinputintodataminingsys- of a BI system is an important issue and must be carefully
tems for data analysis so that decision makers can obtain useful planned. It can serve as the criteria for BI system selection and
informationpromptlyformakingcorrectjudgment;thatis,inre- implementation. However, current research has not yet pointed
gardtoenterpriseoperatingcontents,abilitiesoffastunderstand- outtheeffectivenessanditsassessmentmethodsafterBIsystem
inganddeducingareprovided,andthusenhancingthequalityof actuallygoesonline.Therefore,throughliteraturediscussion,this
decision-makingandimprovingperformanceandexpeditingpro- researchsummedup40criteriaofevaluatinginformationsystem
cessing speed (Back, 2002). Business intelligence is an analysis performances. Proper key criteria are then picked out through
mechanismbywhichautomateddecision-makingregardingbusi- experts’ questionnaires as the major basis for constructing BI
4137
system performance assessment model. This paper proposes to hierarchy, consisting of network relationships between elements
apply ANP method to construct an integrated performance andclusters.
evaluation model for BI systems. ANP method was proposed by ThenetworkrelationshipofANPmethoddoesnotonlypresent
Saaty and Takizawa (1986), and it is an extension of analytic the relationship between rules, but also calculate the relative
hierarchyprocess (AHP).Inreality, theelementswithin thehier- weightings(characteristicvectors)ofeachrule.Theresultofthese
archy of various criteria are often interdependent, but low-level computationsformsasupermatrix.Finally,afterthecomputation
elements may dominate high-level ones. A feedback relationship of the relationship of the super matrix and the comprehensive
also exists in the process, thus, this structure resembles a evaluations, it is possible to derive the interdependence of each
network system. valuation criteria and options and the weighting of priorities.
ThenetworkrelationshipofANPmethoddoesnotonlypresent The higher the priority weightings, the more priority will be
thedependenciesbetweencriteria,butalsocalculatetherelative placed.Inthis manner,it ispossibletoselect themostappropri-
weights(eigenvectors)ofeachcriterion.Theresultofthesecompu- ate option (Saaty, 2003). In the previous literature regarding the
tationsformsasupermatrix.Aftercomputationoftherelationship application of ANP method, Saaty and Takizawa (1986) uses the
betweenthesupermatrixandthecomprehensiveevaluations,itis matrix applications to solve the network structure of ANP meth-
possibletoderivetheweightvaluesbetweencriteriaandalterna- od,inasimilarwaytoAHPmethod.However,theirapproachcon-
tives.Thehighertheweights,themoreprioritywillbeplaced.In siderstheinterdependencebetweenrulesandoptions.Meadeand
thismanner,itispossibletoselectthemostappropriatealternative Sarkis(1999)proposedthe useof ANPmethod toconductpolicy
(Saaty,1996).JharkhariaandShankar(2007)usedANPmethodto analysis in order to evaluate projects so that organizations be-
selectdistributionserviceproviders.TheyindicatedthatANPmeth- come more swifter and better in improving procedures and
oddoesnotonlyestablishabetterunderstandingofthecomplex achieving specific targets. Lee and Kim (2000) applied Saaty’s
relationshipbetweencriteriaindecisionmaking,butalsoimproves ANP method in the selection of IT systems in order to respond
thereliabilityofdecision-making.Chungetal.(2005)adoptedthe to the interdependency of the valuation rules and feasible
matrixmethodproposedbySaatyandsuggestedasimplifiedANP projects.
structuretoanalyzetheinputsandoutputsofmanykindsofpro- JharkhariaandShankar(2007)usedANPmethodtoselectdis-
ductionprocesses.Thebestproductmixcanbederivedbyintegrat- tributionservicesproviders.TheyindicatedthatANPmethoddoes
ingexperts’opinions.ANPmethodismostlyappliedintheselection notonlyestablishabetterunderstandingofthecomplexrelation-
ofmultiple feasiblealternatives, suchas resourceallocationsand ship between valuation criteria in decision-making, but also im-
sequencing,toimprovethereliabilityofdecisionsintheevaluation proves the reliability of decision-making. Chung et al. (2005)
process(Jharkharia&Shankar,2007;Lee,Chen,&Chang,2006;Lin, adopted the matrix method proposed by Saaty and suggested a
Chiu,&Tsai,2008).Inthispaper,detailsoftheANPtechniquewill simplifiedANPstructuretoanalyzetheinputsandoutputsofmany
notbediscussed.However,Section3willpresentanapplicationof kindsofproductionprocesses.Thebestproductmixcanbederived
the ANP technique to the assessment of business intelligence byintegratingexperts’opinions.Fromthepreviousliterature,we
systems. knowthatANPmethodismostlyappliedintheselectionofmulti-
plefeasibleoptions,suchasresourceallocationsand sequencing,
in order to improve the reliability of decisions in the evaluation
3.Researchtheoryandmethod
process(Jharkharia&Shankar,2007).Therefore,thisstudyapplies
ANPmethodtoconstructanassessmentmodeltoeffectivelyeval-
Thisresearchmethodisconsistedofthreeparts.Thefirstpart
uatetheperformancesofBIsystems.
chooses the factors that influence the BI system’s effects as the
foundation of the ANP analysis method. In this section, we sort
out the key elements that influence the effects of information 3.2.ANPdecision-makingflowchart
systems after gathering kinds of documents, and resort to the
experiences and opinions acquired from questionnaire for ex- Step1: Definitionofpolicyissuesandestablishmentofpolicy-making
perts. The second part adopts the selected elements to build up members
the ANP model. The third part is for case study. Based on the All the factors that may affect policy issues should be
analysis result of the ANP model, the contents of interview are incorporated based on the nature of the policy issues, in
designed, the experiences of the studied company implementing ordertodefinethedomainofdiscussions.Abodyofdeci-
the BI system and the effects after the implementation are pre- sionmakersshouldbeestablishedinordertocollatethe
sented, and subsequently, we verify that the effectiveness of opinions of the experts in the relevant fields, based on
the ANP structure built up in this research in the appraisal of a the level of complexity, and the fields of domain issues
BI system. involved.Generally,thenumberofsurveyedexpertshould
notbetoomuch,5–50isasuitablenumber(Reza&Vass-
3.1.ANPtheoryoverview ilis,1988).
Step2: Constructionofthenetworkhierarchylayerstructureofthe
ANP method was proposed by Saaty (1996) in 1975. It is an problems
extension of analytic hierarchy process (AHP). In reality, the ele- Afterconsolidatingandcategorizingrelevantinformation,
mentswithinthehierarchyofvariousrulesareofteninterdepen- keyissuesthataffectthedecisionsareidentified.Thenet-
dent. Low-level elements also dominate high-level elements. work hierarchy layer valuation model is illustrated in
There is a feedback relationship. In such instances, the structure Fig. 2. In the structure, there exists interdependency
ofasystemresemblesthatofanetwork.ANPmethodisstemmed withineachlayerandlooparcsareusedtoindicatefeed-
from this type of network system structure (Wang, 2005). Fig. 1 backrelationships.
illustrates the structural relationship of ANP method (Wang, Step3: Questionnairesurveysandexpertpreferenceintegration
2005).Thissystemcanbedividedintotwoparts.Thefirstpartis Accordingtothenetworkhierarchylayervaluationmodel
thecontrolhierarchy,consistingofnetworkrelationshipsbetween structuredforthedecisionissues,weightingsaregivento
thegoal,criteriaandsub-criteria.Thecontrolhierarchyaffectsthe each element according to their corresponding upper
internalrelationshipsofthesystem.Thesecondpartisthenetwork elements via questionnaires issued to experts to gather
4138
Objective
Criteria
Control
Level
Sub-Criteria
Group C Group C
1 2
Network
Group Group Level
Group C
N
The example of a network structure of sub-criteria
Fig.1. StructuralrelationshipofANPmethod.
Desired Objective Objective
Criteria 1 Criteria 2 …… Criteria N Performance
Measurements
Alternative 1 Alternative 2 … Alternative M Alternatives
…
Represents inter- relationships of performance measurements
Fig.2. ANPnetworkhierarchylayervaluationmodelarchitecture(Saaty,1996).
opinions regarding the relative importance of different ratios (C.R.) of the comparison matrixes. The C.R. of a
elements. If there are a number of experts involved in pairwisecomparisonmatrixistheratioofitsconsistency
theevaluation,averagescanbeusedtocomputethecol- indextothecorrespondingrandomvalue.Thedetailscan
lective weightings. When it comes to the integration of befoundinSaaty’s(Saaty,2005).
expert preferences, Saaty (1980) thinks that geometrical Step6: Computationsofsupermatrixes
averagesyieldbetterresults. Asupermatrixlistsdownallthesub-matrixesconsisting
Step4: Establishment of pairwise comparison matrixes of all the clusters and necessary elements in the order
After the consolidation of judgments and preferences ontheleftanduppersidesofthematrix.Iftheaggregate
from various experts, it is possible to construct a com- ofthecolumnvectorsofasupermatrixisnotequalto1,it
parisonmatrixofmultiplevaluationcriteriaandoptions. iscalledanun-weightedsupermatrix,whichmaybecon-
ANP method applies a measurement of 1–9 and derives verted with specific procedures to make it a weighted
relative weightings based on this measurement. These supermatrix.Afterwards,thematrixwillbelimited,and
weightings then are entered as values of the super gradually the consolidation of the interdependency and
matrix structure so as to reflect the interdependency relativeweightingswillbederived(Saaty,1996).
and relative importance of each valuation criteria and Step7: Selectionofmostoptimaloptions
option. Desirabilityindex(DI)isusedtodeterminethemostopti-
Step5: Consistencytest maloptions.Theformulaisasfollows:
IntheANPmethod,decisionmakersorexpertswhomake
Xr Xr
judgments or preferences must go through the consis- DIi¼ Sij¼ RjWij; 8i; j¼1;2;...;r; ð1Þ
tencytest,whichareconductedbasedontheconsistency j¼1 j¼1
4139
whereDI isdenotesexpectedindicatorofthenumberioption;S is Themajorcriteriawhichinfluencethegoalincludefunctionsofa
i ij
denotestheweightingofnumberioptionunderthecriteriaofnum- BI system (FBIS), service and integration ability (SIA), meeting
berj;R isdenotestherelativeweightingofnumberjsub-criteria; user’sneeds(MUN)andmeetingenterprisesrequirements(MER),
j
W isdenotestherelativeweightingofnumberioptionundernum- andtheyareinteractedandinterdependent.Thesub-criteriarefer
ij
berjsub-criteria. to those performance indicators, i.e. system response time (SRT),
system security (SS), output information accuracy (OIA), imple-
Theoptionwiththehighestvalueofexpectedindicatorsisthe
menting experiences of consultant (IEC), comprehension degree
mostoptimaloptionA*:
toimplementer’sbusiness(CDIB),supportdegreeofusersandhigh
A(cid:2)¼fAjDI ¼maximum ðDI Þg: ð2Þ
i i k¼1;2;...;n k management level (SDUH), conformity to the requirement (CR),
support of organizational efficiency (SOE) and support in deci-
sion-makinginorganization(SDM).
4.BusinessintelligenceANPperformanceassessmentmodel
4.1.Selectionofimpactfactors
5.Empiricalresearchandanalysis
The ANP assessment model is aimed to assist enterprises to
5.1.Expertquestionnaire
evaluatetheeffectivenessofaBIsystem.Itprovidestheeffective
check and the effective analysis to those enterprises that have
This paper utilizes ANP model to design expert questionnaire,
implementedoraregoingtoimplementaBIsystem,andimproves
andappraisestherelativeimportanceofcriteriaasnumbersusing
theusabilityandsatisfactionofBIsystem.Inthisresearch,thekey
thefundamentalscaleoftheAHP,showninTable2(Saaty,2005).
elements that influence the performances of an information sys-
Inthequestionnairedistributionphase,toavoidanyambiguity
temareconstructedafterinterviewingthoseseniorsintheinfor-
orhardreadabilitythatmayaffecttheexternalnatureofanswers
mation department of industrial sectors and listening to the
given by the interviewees, and to facilitate the understanding
visionsandopinionsofexperts.Theambiguousandunsuitablefac-
aboutthisANPmodel,ourresearchersphysicallyvisitedtheinter-
torsinthequestionnairearemodifiedordeleted.Finally,theques-
viewees to make an on-site survey. The projection presentation
tionnaireconsistsoffourcategoriesofcriteria,i.e.functionofaBI
and comparison of criteria was utilized to expedite the under-
system,serviceandintegrationability,meetinguser’sneeds,and
standing of the meaning and contents in the questionnaire by
meetingenterprisesrequirements,andincludesatotalof26ques-
thoseinterviewees.RezaandVassilis(1988)pointedoutthatthe
tions, designed with the Likert-type scale. Twelve copies are re-
numberofexpertsasintervieweeshouldnotbetoomuch,andin
leased,andninevalidcopiesarerecovered.Thereturnrateis75%.
general,5–15personsarebestsuited.Therefore,ourestimateddis-
Byfollowingtheopinionsfromexperts,wechoosenineperfor-
tributionnumberof questionnaires was allocated as threecopies
mance indicators. Of the nice indicators, system response time,
forimplementationconsultantsand12fortheuser-sidethathave
system security, and output information accuracy belong to the
implementedtheBIsystem.Amongthelattertargets,ninecopies
criteria of functions of a BI system, while implementing experi-
weredistributedtotheITpersonnelandthreetoendusers.Thefi-
encesofconsultant,comprehensiondegreeofimplementer’sbusi-
nalparticipatesofsurveywere12,amongthem,threewerecon-
ness are for the criteria of service and integration ability. The
sultants, seven were IT persons and two were end users. The
indicators of the criteria of meeting user’s needs include support
returnratewas80%.
degreeofuserandhighmanagementlevelandconformitytothe
Thesub-criteriaintheANPmodelaresubjecttodiscussionand
requirements.Finally,supportoforganizationalefficiencyandsup-
conclusionthroughrelevantdocumentsandfinallyarescreenedby
port in decision-making in organization are the indicators of the
experts.Inaddition,thedesignofthequestionnairehasbeenau-
criteriaofmeetingenterpriserequirements.Afterdiscussionwith
ditedanddiscussedbyBIexpertswithrichexperiencesformodi-
BIexpertsandmanagersintheinformationdepartment,theinter-
fication or correction. Thus, we believe the questionnaire in this
dependencyamongthosenineperformanceindicatorsasthesub-
researchissomewhatinexpert’sconsideration.TheCronbach’ava-
criteriacanbeobtained,asshowninTable1.
lue ofthequestionnairesis 0.8225,whichmeans theANPexpert
questionnaireexhibitshighreliability(Saaty,2005).
4.2.ANPperformanceassessmentmodel
5.2.TheresultsofBIperformanceevaluationmodel
Inthispaper,thegoaloftheANPperformanceassessmentmod-
el(Fig.3)isdefinedas‘assessingtheperformanceofaBIsystem’.
Through real examples, this research verifies the ANP-based
business intelligence performance assessment model. As criteria
Table1
Theinterdependencybetweenselectedindicators havemadethepair comparisona great deal,wecanonlychoose
severalcomparisonmatrixesassamples.Inthisresearch,thesuper
Criteria Criteria
decisionsoftwareisusedtodefinetheBIperformanceassessment
1 2 3 4 5 6 7 8 9
model.
p p p p
1.Systemresponsetime
p p p p
2.Systemsecurity p p p p p 5.2.1.Pair-wisecomparisonsofmajorcriteria
3.Outputinformationaccuracy
p p p p p UnderthekeyfactorsthatinfluencetheeffectsofaBIsystem,
4.Implementingexperiencesof
consultant theexpertsappraisetherelativeimportanceamongthefourper-
p p p p p
5.Comprehensiondegreeof formance indicators (major criteria). The appraisal results are
implementer’sbusiness p p p shown in Table 3. The matrix showing pair-wise comparisons of
6.Supportdegreeofuserandhigh
majorcriteriaalongwiththeeigenvector(e-vector)oftheseindi-
managementlevel
7.Conformitytotherequirements p p p p p p p p catorsisshowninTable3.
p p p p p p
8.Supportoforganizationalefficiency In order to ensure the consistency of experts’ judgments, the
p p p p
9.Supportindecision-makingin consistency checks must be conducted. Table 3 lists the result of
organization thepaircomparisonmatrixes.TheC.R.=0.0134,whichislessthan
p
Note: meansthattheinteractionexistsamongcriteria. 0.1, is an indication of the consistency of experts’ evaluations
4140
Goal Major criteria Selected Indices
SRT
Functions of BI system
(FBIS) SS
m
e
st
y OIA
s
I
B
f a Service and Integration IEC
o
e Ability (SIA)
c
n
ma CDIB
r
o
f
r
pe Meeting User’s Needs SDUH
e
h (MUN)
g t
n CR
si
s
e
s
s
A Meeting Enterprise SOE
Requirements (MER)
SDM
Fig.3. BusinessintelligenceANPperformanceassessmentmodel.
Table2 With the weight value (the eigenvector), we can have the
Definitionanddescriptionoftheninegradesappraisalscale
weight of each criterion in the target, as is shown in matrix A
Intensityof Definition Explanation below.
Importance
20:0953
1 Equalimportance Twofactorscontributeequally
60:2477
totheobjective A¼6 7: ð3Þ
2 Weakorslight 640:28875
3 Moderateimportance Experiencesandjudgement
0:370
slightlyfavoronefactorover
another
4 Moderateplus
5.2.2.Pair-wisecomparisonsofinterdependenciesofmajorcriteria
5 Strongimportance Experiencesandjudgement
stronglyfavoronfactorover Tounderstandtheinterdependenciesofthemajorcriteria,the
another pair-wisecomparisonmust bemade amongthemajorcriteria to
6 Strongplus obtainthe weights of all the criteria of the goal. From Table4, it
7 Verystrongordemonstrated Anfactorisfavoredvery
importance stronglyoveranother;its
dominancedemonstratedin
practice
Table4
8 Very,verystrong
Pair-wise comparison among major criteria for enhancing functionalities of BI
9 Extremeimportance Theevidencefavoringonfactor
Systems
overanotherisofthehighest
possibleorderofaffirmation Service Meeting Meeting Eigenvector
Reciprocals Iffactorihasoneoftheabove Arationalassumption and user’s enterprises
ofabove nonezeronumbersassignedtoit integration needs requirements
whencomparedwithfactorj, ability
thenjhasthereciprocalvalue
Serviceandintegration 1 0.929 0.540 0.254
whencomparedwithi
ability
Meetinguser’sneeds 1.077 1 0.562 0.270
Meetingenterprises 1.854 1.781 1 0.476
(Saaty,1980).Theresultalsodemonstratesthattheenterprisehas requirements
implementedtheBIsystemtomeetenterprises’requirements. Note:C.R.=0.0001.
Table3
Pair-wisecomparisonsamongperformanceindicatorsunderassessingtheperformanceofBIsystem
FunctionsofaBIsystem Serviceandintegration Meetinguser’sneeds Meetingenterprises Eigenvector
ability requirements
FunctionsofaBIsystem 1 0.418 0.262 0.300 0.095
Serviceandintegrationability 2.393 1 0.874 0.730 0.247
Meetinguser’sneeds 3.823 1.1436 1 0.618 0.288
Meetingenterprises 3.377 1.370 1.617 1 0.370
requirements
Note:C.R.=0.0134.
4141
shows that the importance level of meeting enterprises require- valuesrepresenttherelativeweightingofeachselectedindicators
ments on the functionality enhancement of BI system is 1.781 comparedtothatofthemajorcriterion.Wecandiscoverfromthe
timeshigherthanthatofmeetingusers’needs.Otherfigurescan matrixCthatitissuitabletodesignevaluationindicatorsforthe
be interpreted in same way. Thus, we can have the comparative OIA, IEC, UECC and MR criteria if the effects of a BI system is to
weightvaluesaftercomparisonofprimarycriteria.Therefore,un- beevaluated
der the criterion of FBIS, the relative weight values for ESIP, 20:114 3
MUN,andMERare(0.254,0.270,0.476),respectively.
60:242 7
ThefiguresshowthattheperformanceindicatorsofMERhave 6 7
the greatest impacton the FBIS while the ESIP influencesless. In 660:644 77
6 7
addition,theC.R.valueis0.0001andislessthan0.1,whichmeans 66 0:623 77
6 7
the appraisal result of experts is consistent. By resorting to the C¼6 0:377 7: ð5Þ
6 7
samemethod,wecanhavetheimportancelevelandthecompar- 6 0:722 7
6 7
ison figures. The results are shown in matrix B of formula 4, in 66 0:278 77
which the values in matrix represent the weights value of those 66 0:21477
4 5
criteria
0:789
2 0 0:328 0:135 0:1223
60:254 0 0:334 0:4037
B¼6 7: ð4Þ 5.2.4.Pair-wisecomparisonamongselectedindicators
640:270 0:331 0 0:47575 InTable6, thefigurein theblockof secondcolumnand third
0:476 0:431 0:531 0 row means the importance of IEC is 2.44 times that of the CDIB.
With same manner, we know the importance comparison pairs.
From the matrix we can see that the weight is sequenced in this
TheresultisshowninthematrixDofformula6,inwhichthefig-
way:1MER,2MUN,3ESIP.Thusweknowthemaintargetsofsur-
uresrepresenttheweightvaluesofselectedindicators.
vey(BIconsultants,ITpersonsandusers)careMERthemost.Ifitis
: ð6Þ
aimedtoimprovetheeffectsafterimplementingBIsystems, MER 5.3.CalculationofmatrixM
shouldhavethehighestpriority.
Theaggregationofall therelativeweightings ofthe pair-wise
5.2.3.Pair-wisecomparisonoftheselectedindicatorsundermajor comparisonmatrices(formula3–6)derivestheun-weightedsuper
criteria matrixM(showninTable7)oftheBIsystemassessmentmodel.
The three detailed indicators, SRT, SS, and OIA, affect the However,thesupermatrixMdoesnotmeetwith‘‘columnstochas-
enhancementoftheBIfunctions.Thecomparisonresultbetween tic”limitation,i.e.thesumofeachofthecolumnmustbe1.Itis
theimportanceofSRT,SSandOIAandtheimportanceofFBIS(ma- necessarytocomputeappropriateweightingssothattheaggrega-
jorcriterion)intheexpert’sassessmentisshowninTable5. tionofallthecolumnvalueswillbeequalto1.Afterperforming
InTable5,itshowsthatOIAis6.601timesmoreimportantthan necessaryoperationsforthelimitationoftheweightedsuperma-
SRTfortheenhancementofBIfunctionality.Underthecriterionof trix,theconvergedsupermatrixM0isderived.Asthesumofrows
enhancingthefunctionsofaBIsystem,therelativeweightingsof lessthan1iscalledtheun-weightedmatrix,weaddsomecertain
SRT,SS,andOIAare0.114,0.242,and0.644,respectively.Thecom- weightstomakethesumequalto1andobtainaweightedmatrix
parisonofimportancelevelsofotherscanbeobtainedinthesame M0,Table8.Afterthelimitationsoftheweightedsupermatrix,the
manner.Theresultisshowninthematrixofformula5,wherethe convergedsupermatrixM00 isderived,asshowninTable9.
Table6
Table5 Pair-wisecomparisonofperformanceindicatorsunderSRT
Pair-wisecomparisonofperformanceindicatorsunderFBIScriterion
IEC CDIB CR SOE Eigenvector
SRT SS OIA Eigenvector
IEC 1 2.44 1.70 1.23 0.348
SRT 1 0.553 0.152 0.114 CDIB 0.409 1 0.373 0.444 0.119
SS 1.811 1 0.440 0.242 CR 0.587 2.678 1 0.715 0.241
OIA 6.601 2.274 1 0.644 SOE 0.813 2.253 1.398 1 0.292
Note:C.R.=0.0239. Note:C.R.=0.0157.
4142
Table7
Theun-weightedsupermatrixM
Goal Majorcriteria Selectedindicators
0.0Assessingthe 1.1 1.2 1.3 1.4 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9
performanceofBI FBIS SIA MUN MER SRT SS OIA IEC CDIB SDUH CR SOE SDM
system
Goal 0.0Assessingthe 0 0 0 0 0 0 0 0 0 0 0 0 0 0
performanceofaBI
system
Major 1.1FBIS 0.095 0 0.238 0.135 0.122 0 0 0 0 0 0 0 0 0
criteria 1.2SIA 0.247 0.254 0 0.334 0.403 0 0 0 0 0 0 0 0 0
1.3MUN 0.288 0.270 0.331 0 0.475 0 0 0 0 0 0 0 0 0
1.4MER 0.370 0.476 0.431 0.531 0 0 0 0 0 0 0 0 0 0
Selected 2.1SRT 0 0.114 0 0 0 0 0 0 0.093 0.081 0 0.062 0.065 0
indicators 2.2SS 0 0.242 0 0 0 0 0 0 0.132 0.121 0 0.078 0.088 0
2.3OIA 0 0.644 0 0 0 0 0 0 0.360 0.374 0 0.204 0.280 0.347
2.4IEC 0 0 0.623 0 0 0.348 0.331 0.243 0 0.183 0 0.092 0 0
2.5CDIB 0 0 0.377 0 0 0.119 0.138 0.177 0.150 0 0 0.056 0 0
2.6SDUH 0 0 0 0.722 0 0 0 0 0 0 0 0.210 0.230 0.329
2.7CR 0 0 0 0.278 0 0.241 0.350 0.205 0.265 0.241 0.201 0 0.146 0.145
2.8SOE 0 0 0 0 0.214 0.292 0.181 0.158 0 0 0.249 0.135 0 0.179
2.9SDM 0 0 0 0 0.786 0 0 0.217 0 0 0.550 0.163 0.191 0
Table8
TheweightedsupermatrixM0
Goal Majorcriteria Selectedindicators
0.0Assessingthe 1.1 1.2 1.3 1.4 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9
performanceofBI FBIS SIA MUN MER SRT SS OIA IEC CDIB SDUH CR SOE SDM
system
Goal 0.0Assessingthe 0 0 0 0 0 0 0 0 0 0 0 0 0 0
performanceofaBI
system
Major 1.1FBIS 0.095 0 0.119 0.068 0.061 0 0 0 0 0 0 0 0 0
criteria 1.2SIA 0.247 0.127 0 0.167 0.201 0 0 0 0 0 0 0 0 0
1.3MUN 0.288 0.135 0.165 0 0.238 0 0 0 0 0 0 0 0 0
1.4MER 0.370 0.238 0.216 0.265 0 0 0 0 0 0 0 0 0 0
Selected 2.1SRT 0 0.057 0 0 0 0 0 0 0.093 0.081 0 0.062 0.065 0
indicators 2.2SS 0 0.121 0 0 0 0 0 0 0.132 0.121 0 0.078 0.088 0
2.3OIA 0 0.322 0 0 0 0 0 0 0.360 0.374 0 0.204 0.280 0.347
2.4IEC 0 0 0.311 0 0 0.348 0.331 0.243 0 0.183 0 0.092 0 0
2.5CDIB 0 0 0.189 0 0 0.119 0.138 0.177 0.150 0 0 0.056 0 0
2.6SDUH 0 0 0 0.361 0 0 0 0 0 0 0 0.210 0.230 0.329
2.7CR 0 0 0 0.139 0 0.241 0.350 0.205 0.265 0.241 0.200 0 0.146 0.145
2.8SOE 0 0 0 0 0.107 0.292 0.181 0.158 0 0 0.249 0.135 0 0.179
2.9SDM 0 0 0 0 0.393 0 0 0.217 0 0 0.551 0.163 0.191 0
5.4.Selectionofthebestevaluationindicator betweenthetwogroupsofexperts.TheresultisshowninTables
11and12.
Theselectionofthebestalternativedependsontheoutcomeof InTables11and12,theresultsshowthattheaverageweight
thedesirabilityindex(DI),showninTable10.AccordingtotheDIs priority sequences are identical between the technical experts
showninTable10,thelargerthepriorityweighting,thehigherthe and the end users. Among the indicators, the most addressed is
priorityofbeingadoptedis.FromTable10,mostexpertsthinkthe number 2.3-OIA (0.1853, 0.1794), which is followed by number
‘Outputinformationaccuracy’(OIA)canbestevaluatethebenefits 2.7-CR (0.1691, 0.1687) and number 2.9-SDM (0.1559, 0.1628).
of BI. The OIA indicator is also the most concerned one for users The SRT is the least important item. Thus, we can see that both
and consultants to improve the total benefits of BI systems. The the technical experts and the end users have identical opinions
‘conformitytotherequirements’(CR)ranksthesecond,and‘sup- ontheconclusionofperformanceevaluationindicatorsfromthis
portindecision-makinginorganization’(SDM)thethird.‘system research.Thoseassessmentindicatorscanbeutilizedasthebasics
response time’ (SRT) is believed to be hardest factor to appraise forthecompaniedintendingtoimplementorimplemented.
thebenefitsresultedfromBIsystems.
5.6.Summary
5.5.Analysisofcriteriaweightings
The above analysis shows that there is little difference on the
To make effective judgment on the results of the ANP model importance of the nine performance indicators between experts
analysis, those experts in survey are divided into two groups. withdifferentbackgrounds.FortheeffectsoftheBIsystem,they
One is those with technical background (including consultants regard OIA as the first priority indicator, followed by CR and
and IT personnel) and the other is end users. We have made an SDM,andetc.ItdemonstratesthatbothITpersonnelandendusers
analysistosee if thereis anydifferenceon theprioritysequence expectaccurateinformationfromtheBIsystem.Thus,toimprove
4143
Table9
TheconvergedsupermatrixM00
Goal Majorcriteria Selectedindicators
0.0Assessingthe 1.1 1.2 1.3 1.4 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9
performanceofBI FBIS SIA MUN MER SRT SS OIA IEC CDIB SDUH CR SOE SDM
system
Goal 0.0Assessingthe 0 0 0 0 0 0 0 0 0 0 0 0 0 0
performanceofaBI
system
Major 1.1FBIS 0 0 0 0 0 0 0 0 0 0 0 0 0 0
criteria 1.2SIA 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1.3MUN 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1.4MER 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Selected 2.1SRT 0 0 0 0 0 0 0 0 0 0 0 0 0 0
indicators 2.2SS 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034 0.034
2.3OIA 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046 0.046
2.4IEC 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185
2.5CDIB 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100 0.100
2.6SDUH 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067 0.067
2.7CR 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116 0.116
2.8SOE 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169 0.169
2.9SDM 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127 0.127
Table10 6.1.Casebrief
Thedesirabilityindex(DI)andsequenceofassessingcriteriaforBIsystems
ThecompanyinthecasewasfoundedintheUSin1981,andisthe
Performancecriteria DI Sequence
largestsupplierofcomputerperipherals.Thecompanyhassetupits
2.3OIA 0.1853 1
operationcentersinSwitzerland,HongKongandTaiwan.Listedin
2.7CR 0.1691 2
2.9SDM 0.1559 3 NASDAQ, with 7200 employees, the company has products like
2.8SOE 0.1270 4 internet cams, input devices, multi-media systems, computer
2.6SDUH 0.1161 5 microphones,mobilephoneearphones,bluetoothearphone,recrea-
2.4IEC 0.0998 6
tiondevicesandotheritemswithhumaninterfacedevices.Inthis
2.5CDIB 0.0675 7
research,thesurveytargetsarethemanagersinchargeofproducts
2.2SS 0.0457 8
2.1SRT 0.0336 9 manufacturedintheHsinchuScience-basedIndustrialPark.
6.2.Analysis
theeffectivenessoftheBIsystem,theaccuracyofresultsshouldal-
This research adopts the manner of interview to know the
waysbeaddresses.Afterall,mistakeninformationdoesnothingfor
varioussituationsthecompanymeetswhenitpromotestheBIsys-
theoperationsofenterprise,andevenworse,itcouldbringfatality
tem.Theintervieweesaretheseniormanagersintheinformation
totheenterprise.
departmentofthecompany.
Questionsintheinterview:
6.Casestudy
1. Systemaspect
ToverifytheeffectivenessoftheANPmodel,westudiedacom- The company has adopted ERP as the tool of data analysis
panythathasimplementedtheBIsystemasanexample.Through beforetheBIsystemisimplemented.Therefore,globalMRPis
theinterview,theprocessofimplementingtheBIsystemandusing executed and material plan is generated. It is a challenge for
informationcanbepresented. the planning job. To improve the planning efficiency, the
Table11
Weightingsanalysisofselectedindicatorsforallexperts
Expert PerformanceindicatorsthatinfluenceoneffectofBIsystem
2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9
E1 0.0336 0.0457 0.1853 0.0998 0.0675 0.1161 0.1691 0.127 0.1559
E2 0.0460 0.0774 0.1604 0.1074 0.0602 0.0548 0.1742 0.2190 0.1006
E3 0.0446 0.0253 0.1587 0.0373 0.0362 0.2070 0.1589 0.1142 0.2178
E4 0.0229 0.0155 0.0757 0.1358 0.1071 0.1490 0.1691 0.121 0.2039
E5 0.0504 0.0230 0.1890 0.1070 0.0213 0.1656 0.1416 0.0956 0.2065
E6 0.0271 0.0507 0.2242 0.0521 0.0921 0.0593 0.1890 0.1770 0.1285
E7 0.0414 0.0725 0.1074 0.0903 0.0631 0.1297 0.2361 0.1309 0.1286
E8 0.0216 0.0363 0.1056 0.1153 0.0344 0.1578 0.1954 0.1507 0.1829
E9 0.0266 0.0696 0.2100 0.1023 0.0958 0.1201 0.0778 0.1037 0.1941
E10 0.0250 0.0368 0.3327 0.1240 0.0368 0.0280 0.1758 0.1315 0.1094
E11 0.0312 0.0521 0.2233 0.1007 0.0931 0.0765 0.2042 0.1017 0.1172
E12 0.0332 0.0430 0.2510 0.1260 0.1028 0.1292 0.1382 0.0514 0.1252
Average 0.0336 0.0457 0.1853 0.0998 0.0675 0.1161 0.1691 0.1270 0.1559
Note:E1–E3aretheconsultants,E4–E10aretheITpersonnel,andE11–E12aretheendusers.
4144
Table12
Weightingsanalysisofselectedindicatorsfor10experts
Expert PerformanceindicatorsthatinfluenceoneffectofBIsystem
2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9
E1 0.0336 0.0457 0.1853 0.0998 0.0675 0.1161 0.1691 0.1270 0.1559
E2 0.0460 0.0774 0.1604 0.1074 0.0602 0.0548 0.1742 0.2190 0.1006
E3 0.0446 0.0253 0.1587 0.0373 0.0362 0.2070 0.1589 0.1142 0.2178
E4 0.0229 0.0155 0.0757 0.1358 0.1071 0.1490 0.1691 0.121 0.2039
E5 0.0504 0.0230 0.1890 0.1070 0.0213 0.1656 0.1416 0.0956 0.2065
E6 0.0271 0.0507 0.2242 0.0521 0.0921 0.0593 0.1890 0.1770 0.1285
E7 0.0414 0.0725 0.1074 0.0903 0.0631 0.1297 0.2361 0.1309 0.1286
E8 0.0216 0.0363 0.1056 0.1153 0.0344 0.1578 0.1954 0.1507 0.1829
E9 0.0266 0.0696 0.2100 0.1023 0.0958 0.1201 0.0778 0.1037 0.1941
E10 0.0250 0.0368 0.3327 0.1240 0.0368 0.0280 0.1758 0.1315 0.1094
Average 0.0339 0.0453 0.1749 0.0971 0.0615 0.1187 0.1687 0.1371 0.1628
Note:E1–E3aretheconsultantsandE4–E10aretheITpersonnel.
companyboughtOracleDataWarehouseandsavedthetransac- system is set in the US and India and it is responsible for the
tiondata,customerordersandcostinformationintothedata- coordination and communication with suppliers of BI system.
base. Then, the company bought Business Objects 5.0, which TheITpersonnelintheWorldwideServiceProviderarerespon-
is used to assist managers and users in generating dynamic sibleforlearninganddescribingthespecialskillsforinterface
reports. The BI system is expected to shorten the duration of design, KPI, formulation of cube data and statement format
data processing, to improve the integration and completeness development.Also,theyneedtounderstandthecurrentsitua-
of information, and to catch the data required by the analysis tionsofusers,promotethefunctionsofBIsystems,andenable
forthesubmittaltothesuperior.Toimprovetheeffectsofthe theuserstobeinterestedintheuseofthesystemandwilling
system, the company implemented Oracle 11i at the end of toqueryoranalyzewiththemeansofBItools.TheWorldwide
2004. Now, the IT personnel are active to try to present the ServiceUserincludesoperationsandfinancedepartments,and
information from the BI system in the manner of showing on the managers, who ought to raise their opinions for the KPIs
the war room dashboard, and to enhance the conformity and andtheinterfaces,areofferedwithasetofsuitableanalysistool
resistanceoftheoutputinformationforefficiencyimprovement aftercommunicatingwithITpersonnel.
ofdecision-making. 3. Effectaspect
2. Implementationaspect ByutilizingtheindicatorsandweightingsoftheANPmodel,the
ThecompanyutilizestheBIimplementationteamintheUSand effectivenesscanbecomputedwiththescoresoftheinterview-
IndiatoimplementandintegratetheBIsystemsinthebranches ees through formula 7. The overall effectiveness analysis is
intheglobally.Thus,theleaderofeachbranchmustphysically showninTable13.
visittheUSheadquartersandtheIndiaBranchtoexchangethe X9
demandswithlocalteams.TheKPIs(keyperformanceindices) Wj(cid:3)Gi¼PVi foralli ð7Þ
aregeneratedafterthediscussionandcoordinationamongman- j¼1
agersandITdepartmentpersonnelineachbranchcompanyand WjistheweightingofNo.jassessmentindicator(j=1,2,...,9).
thustheyhavehighreferencevalue.Theparticipantsanduseof GiisthescorefromtheNo.iinterviewee.PViistheeffectiveness
BIsystemareshowninFig.4. FromFig.4,thedesigncenterofBI recognizedbyNo.iintervieweefortheBIsystem.
Design Center
BI implementation team
(InUS and India)
Fulfill Requirements Feedback
Deliver designed BI system Deliver requirements and
to branch company World Wide Service Provider discuss with BI team
Local IT Department
Training Propose Requirements
Teach end users Deliver requirements and
World Wide Service User discuss with BI team
Functional Department
Fig.4. ParticipantsanduseofBIsystem.