Analysis of Business Intelligence on Strategic Decision Making

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Correspondent author: Mohammad AghaeiManuscript No: IJSMD-RJRS-2013-009

International Journal of Scientific Management and Development ISSN:2345-3974Vol.2 (1), 20-35, November (2013)

Review Paper

Analysis of Business Intelligence on Strategic Decision MakingMohammad Aghaei 1, Amin Asadollahi 2

1. Assist Prof, Department of Business Management, Branch, Tarbiat Moddares University, Tehran, Iran2. Department of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

Available online at: www.IJSMD.ComReceived 25th Oct 2013, revised 1th Nov 2013, accepted 6th Nov 2013

Abstract

Today, it is needed to use appropriate ICT tools such as business intelligence systems in scientific management of organizations. Themain objective of this study was to investigate the relationship between Business Intelligence systems and systems to support strategicdecisions. Business intelligence can be defined, not as a tool or a product or even a system, but as a new approach in organizationalarchitecture based on speed in analysis of information in order to make accurate strategic decisions in business in minimum amount oftime with maximum quality. In this research, after a review of studies done in the past, a conceptual model of the effect of businessintelligence on strategic decisions has been designed and with providing questionnaire and distribution of the questionnaire among theelite experts in business intelligence in the office of undersecretary of information technology and communication of the ministry ofindustry, mining and business and the scientific society of E-commerce in Iran, reliability and validity of the presented model wereassessed. Factor analysis, correlation analysis and structural equations in LISREL and SPSS statistical software were used in order toanalyze the results of the assessment. The results show that business intelligence can improve strategic decisions; and it can havesignificant positive effects on aspects of strategic decisions such as efficiency, effectiveness, agility, flexibility and integration. At theend of the study, based on the hypotheses of the research, some suggestions have been presented to expand the utilization of businessintelligence in organizations and also to conduct future studies.

Keywords: Business Intelligence, Strategic Decision Making, Decision Support Systems (DSS), Online Analytical Processing(OLAP), Competitive Intelligence, Data Mining.

1. Introduction

The term Business Intelligence was introduced by GartnerGroup in the mid-1990s. However, this term has become verypopular recently and it has its roots in the MIS reporting systemsof 1970s. In that era, static reporting systems were two-dimensional and did not have the analytical capability. In theearly 1980s, the concept of executive information systems (EIS)came into existence. This concept introduced computerizedsupporting systems to high-level managers and executive board.These systems had the capabilities of dynamic and multi-dimensional reporting (ad hoc or desire based), forecasting,trend analysis, analyzing the details and access to the keyelements of successfulness. Until the mid-1990s, manycommercial products used to have these features. Then somenew products have been established in the name of businessintelligence. Today, all of them have concluded that all theinformation needs of executives can be complied in the form ofan information system based on Business Intelligent (Gartner,2007).

Therefore, the main concept of executive information systemwas changed into business intelligence. By 2005, business

intelligence systems were equipped with the capabilities ofartificial intelligence and high analytical abilities.

This study aimed to investigate the effect of BusinessIntelligence (BI) on organizational strategic decisions.Organizational strategic decisions are decisions that are lessfrequent and which are taken for prolonged periods, but areassociated with high volumes of data and processes. Decisionsmade in these levels are often in unstructured problems and aremade by senior managers; and the results have long-termimpacts in the path of the organizations (Pierce and Robinson,1998).

Regarding what is mentioned, Business Intelligence is a conceptwhich includes architecture, tools, database, applications andmethodology of managing the operations of businesses; and itcan lead to better decision making. Thus, in this study, theeffects of Business Intelligence (BI) on organizational strategicdecisions will be discussed.

The model of Pressure-Response-Support in business is used toevaluate the impact of business intelligence on organizationalstrategic decision making, (Figure 1).


21International Journal of Scientific Management and Development

Figure (1). Model of Pressure-Response-Support in Business, Zaman, 2005

Based on this model, the dynamicity of pressures imposed to theorganization and the opportunities provided affect the strategicdecisions. Business intelligence systems support theorganizational decisions as an automatic and intelligent systemand lead to improve the responsibility of organization; and theycan affect the flexibility, alignment of the decisions to the goals,decision accuracy, agility, integrity, effectiveness and efficiencyof decision-making (Zaman, 2005).

The term Business Intelligence has become prevalent by GartnerGroup in the mid-1990s. However, the term has become verypopular recently and it is rooted in the 1970 MIS reportingsystems. In that era, static reporting systems were two-dimensional and did not have analytical capabilities. In the early1980s, the concept of executive information systems came toexistence. This concept introduced computerized supportingsystems to high-level managers and executive board. Thesesystems had the capabilities of dynamic and multi-dimensionalreporting (ad hoc or desire based), forecasting, trend analysis,analyzing the details and access to the key elements ofsuccessfulness. Until the mid-1990s, many commercial productsused to have these features. Then some new products have beenestablished in the name of business intelligence. Today, all ofthem have concluded that all the information needs ofexecutives can be complied in the form of an informationsystem based on Business Intelligent (Raisinghani, 2004).

Thus, the original concept of executive information systems waschanged into business intelligence. By 2005, the businessintelligence system reached the capabilities artificial intelligenceand higher analytical abilities (Zaman, 2005).

2. Literature Review

2.1 Decision making and decision supporting systems

Of the critical aspects of management tasks are communication,information collection, and decision making; and controlling the

decisions in an organization. Among these critical tasks,decision making is so important that some authors have definedan organization as a "Network of decisions" and management as"the practice of decision making" (Tohidi, 2011). Withoutdecision no new action or activity starts and no aim is achievedin an organization. In changing policies, development ofobjectives, organizational planning, selections, evaluations andall actions of management, decision making is needed. Themanagers are responsible for their decisions. In fact, managershave always been involved with this issue and ultimately thesuccesses and failures in the implementation of decisions maketheir future (Tohidi, 2011). Among the types of decisions,strategic decisions are the most important, because the futureand long-term goals of the organizations are based on thesedecisions; and because they are long-term decisions, they aremade in the situation of uncertainty and with uncertaininformation. Strategic decisions are the basis for future andlong-term planning in organizations. In fact, the success orfailure of any organization depends on strategic decisions thatmanagers can make in the present for the future (Hamidizade,2009).

2.2. Strategic decision

Decisions of high-ranked managers are made in the situation ofuncertainty, because they are about future and they are long-term decisions that make organizations having goals anddirections. These decisions are made optionally and non-continuous and are often complicated, widespread and havinguncontrolled variables and they are affected by complexity,degree of formality, level and degree of focus in an organization(Hamidizade, 2009). In other words, strategic decisions aredecisions that cannot be taken and implemented independent ofthe environment (Lee, 2005). In fact, aspects that make strategicdecisions distinct from other decisions are as follows (Rostami,2009):

Unusual nature and the lack of structure

Globalization

Large Demand

GovernmentalRegularities

Competitive Markets

Dynamicity of theEnvironment and …

Flexibility

Agility

Quality

Integration

Effectiveness

Efficiency

Analysis, Decision,Prediction

Business Intelligence

Business EnvironmentalFactors

Organization’s ResponseDecision and Support



High and especial importance High Complexity Low frequency

From definition of strategic decisions and comparing them toother decisions, it is completely clear that these decisions needmore creativeness and creative managers that have the power forplanning in unknown environmental situations, can make thesedecisions perfectly (Rostami, 2009). What is certain is thatstrategic decisions are unstructured and unconventional (Alvani,2010).

2.3 Decision Support Systems

Decision support systems help managers to make decisions thatare not ordinary decisions and making decisions for them is noteasy for the managers. These systems, in addition to use theorganizational data, may use information from outside theorganization. In these systems, the qualitative and quantitativemodels of decision making and analysis can be used. Thesystem makes a mutual relationship to user so that the user canchange the information and assumptions of decision making orask new questions or provide additional data (Power, 2003).

The history of decision support systems has is a short historyand its concepts and technologies related to it are still inprogress. Many of the old creators and developers are nowretiring, but their comments and actions can be used to obtainnew cases in this area. Internet and the Web raised the speed ofdevelopment in decision support systems and provided a new

way of acquiring knowledge in this field of research (Power,2003).

Nowadays, using the systems based on Business Intelligence hasbecome more common and it has improved the decision makingin organizations. In order to do that, it is necessary to analyzethe business intelligence and its importance in improvingorganizational strategic decisions (Power, 2003).

2.4 Business Intelligence

Business Intelligence is a general concept which includesarchitectures, tools, databases, applications and methodologies(Raisinghani, 2004). This concept is not related to the contentand its meaning varies from person to person. Part of theconfusion in understanding the concept of business intelligenceis caused by clutter in terminology and tools associated withbusiness intelligence (such as management of businessperformance). The main objective of business intelligence is tomake the interactive availability of data (and sometimes during)and data management possible and provides the possibility foranalysts and business managers to carry out their requiredanalyses. Decision-makers, with analysis of current andhistorical data, positions and functions, gain a good perspectiveand they can make better decisions based on this information(Zaman, 2005). Business Intelligence is based on convertingdata to information and then making decision and finally takingaction. Different definitions of business intelligence will beexpressed in this part of the article.

Table (1). Different definitions of BI in the scientific literature

Definition of BIAuthor

Business Intelligence is a tool which is used in order to develop useful information to help organizations inglobal economy and to predict general business environment.

Jourdan et al.(2008)

Business Intelligence is a combination of products, technologies and methods to organize the keyinformation which is used for continuous improvement of profit and performance management oforganizations.

Williams andWilliams (2007)

Business Intelligence is a system which is used to extract knowledge and cognition from structured data andunstructured data.

Ariyachandra, T., &Watson, H (2006)

Business Intelligence is a management philosophy and a tool that helps managing the organizations andmonitoring information in order to effective decision making.Inmon, B. (2008)

It is a system for supporting the decisions that includes tools for data storage, intelligent reporting, onlineanalytical processing, data mining, performance management, predictive analysis and etc.

Wise, L. (2007)

Business Intelligence is a system that is used for utilization of the results of collection, analysis, evaluationand utilization of information in the business realm.

Chang ,E. (2006)

It is a comprehensive system that is used to support decision making.Oracle. (2007)

It is a set of concepts, methods and processes aimed at improving business decisions and also supporting theorganization’s strategy.

Olszak and ziemba(2007)

It is a set of organized and systematic processes which is used for obtaining, analyzing and disseminatinginformation to support effective strategic decision making.

Hostmann, B. (2007)

It is the architecture and a set of integrated processes and also decision support applications that provides thepossibility of access to business data for business communities.

Moss & atre (2003)



In fact, “business intelligence” is a new technology that aftercollection, storage, cleaning, assembly, analysis and informationretrieval, makes the decision making and planning processeasier for managers (Howson, Cindi, 2008). BusinessIntelligence is considered, not as tool or a product or eve asystem, but as a new approach in organizational architecturebased on speed in information analysis in order to makingaccurate and intelligent decisions in business in the minimumamount of time. In fact, it is a set of skills, technologies, useful

systems that are used to collect, store, analyze and provideefficient access to data repositories to help organizations incorrect decision making. Thus, BI can enable us to makedecisions on all effective factors in organizations (Saber, 2009).

3. Research Background

In order to investigate the background of the research, relevantforeign and domestic researches are reviewed and the results arepresented in Table 2.

Table (2). Review of Research Background

ExplanationAuthor

Business Intelligence will reduce wasting costs and time in decision-making and will increasecompetitiveness. Also, Business Intelligence can also increase the speed of decision-making.

Mahmoudi,Mahdi (2008)

Business Intelligence is not just a tool or a product or system, but also a new approach toorganizational architecture based on the speed in data analysis to make smart and accurate businessdecisions in the minimum amount of time. He stated in his studies that business intelligence leads to

accurate and intelligent decision-making among the high ranked managers.

Golestani, Amin(2009)

Business Intelligence solutions can support management decision making at all levels: in the strategiclevel of BI, it will provide the possibility of accurate arrangement of goals and pursuing the

achievement of them. BI provides the possibility of different comparative reports like results ofhistorical reviews, usefulness of special suggestions, effectiveness of the ways for distribution of

information with simulation of the results related to development and prediction of future based onsome presuppositions. At the tactical level, BI may create a basis for decision making complied withfinancial management, human resources management and etc. These systems allow the organizationto be optimistic about future and to correct the technological, financial or organizational functions inorder to realize its strategic objectives and its effectiveness. At the operational level, BI is used for

case analysis and answering the questions related to continuing operations, financial assessments andetc.

Mahmoudi,Mahdi (2009)

Business Intelligence leads to improve overall performance of organization and optimization oforganizational processes and makes the decisions more efficient.

Beikzadeh, Jafar& Eskandari,Karim (2009)

“Business Intelligence” is a new technology that makes the process of deciding and planning formanagers easier after gathering, storing, cleansing, aggregation, analysis, and retrieval of information.Golpaygani,

Majid (2010)

Business Intelligence makes the organizational performance transparent and provides the possibilityof supporting the high-level decisions and it facilitates the better decision making.

Sarrafzadeh,Asghar (2011)

Business Intelligence can contribute to effective decision making.Rohani, Saed &Ghazanfari,

Mahdi (2011)Business Intelligence is a set of applications and technologies for collecting, cohesion and coherence

of the organizational dispersed data and information aimed at increasing the awareness of organizationand improving the decision making process of senior managers.

HaghighatMonfared, Jalal

& ShabanMayani,

Mahbube (2011)Business Intelligence is a system that integrates different dispersed data and it can provide analyticalreports for decision making of high-ranked managers of organization using applicable techniques and

plans.

HaghighatMonfared, Jalal& Malayeri, Ali

(2011)

Business Intelligence is not considered as a tool or a product or even a system, but as a new approachto organizational architecture based on speed in information analysis in order to make accurate and

smart business in minimum amount of time. In fact, it is a set of skills, technologies and applied

Abolghasemzade,Fereidoon (2011)



ExplanationAuthor

systems that can be used for collecting, storing, analyzing and making effective access to the datastores in order to help organizations for making correct decisions. Thus, BI can enable organizations

to make decisions on all factors.

The strategic use of business intelligence can enhance the overall efficiency of the organization andhelp optimization of processes. These systems focus on some important financial features and other

important parameters of increasing the efficiency of the organization.

Dehghani,Mohammad

Javad, Jadidi,Lale (2012)

Business Intelligence is an effective solution for making strategic decisions and it leads to integrityand it enhances the quality of the decisions.

Hosseini, SeyedMahdi &

Rostami, Fateme(2012)

Business Intelligence is a set of integrated operations and also decision support plans and data bankswhich provides the possibility of access to business for business communities.Moss & atre

(2003)

Business Intelligence leads to increase in accuracy of decision making and optimizes the utilization ofthe data in the realm of business.Chang ,E. (2006)

Business Intelligence is a system which is used to extract knowledge from structured data andunstructured data, and it leads to increase the efficiency and effectiveness of the decision-making.

Ariyachandra, T.,& Watson, H

(2006)Business Intelligence leads to improve the performances and increases the profit from decisions.

Williams andWilliams (2007)

Business Intelligence is a broad concept including data storage and reporting, analytical processing,performance management and predictive analysis that improves the quality of decisions and leads to

improve in decision-making.Wise, L. (2007)

Business Intelligence is a tool to support decisions that improves the results at all levels ofmanagement.Oracle. (2007)

Business Intelligence is a set of concepts, methods and processes, that its goal is not only to improvebusiness decisions, but also supports the organization’s strategic objectives.Olszak and

ziemba (2007)

Business Intelligence involves organized and systematic processes of obtaining, analyzing anddisseminating information to support strategic effective decision making.Hostmann, B.

(2007)

Business Intelligence leads to develop enterprise data and helps to improve forecasting and decisionmaking in turbulent environments contributed to global businesses.Jourdan et

al.(2008)

Business Intelligence is a management philosophy and tool which aims at making effectivemanagement and monitoring information.Inmon, B. (2008)

4. Material and Method

There are different kinds of models in the field of businessintelligence applications, architecture and business intelligencetools. However, there is no model to analyze the impact ofbusiness intelligence on strategic decisions. According to theabove review of literature, as well as the review of models ofbusiness intelligence, the research model was designed based onpressure-response model of Toyota. The conceptual model ofresearch which was presented to evaluate the questions andassumptions is explained in Figure 2. According to the pressure-response model of Toyota, because of the dynamicity of theenvironment, pressures are imposed to the organizations andopportunities are provided that affect the strategic decisions.Business Intelligence Systems work as automatic smart decision

support systems in organizations and improve the responsibilityof organization and can affect flexibility, harmony of decisionswith the objectives, the speed and accuracy of decision, agility,integrity, effectiveness and efficiency of decision-making andimprove making strategic decisions (Zaman, 2005). Figure 2shows the conceptual model of research which is designed basedon pressure-response model of Toyota. In order to examine thevalidity of this model, the structural equations method is used inthe results of research which is a new method for evaluation andexamination.



Fig (2). The research Model

Describing the model and variables of the research

Conceptual model of the research is designed based on themodel of pressure-response of Toyota and using a review ofprevious researches. Components and variables of this modelare:

Independent variable

• Business Intelligence: BI is an umbrella-like concept thatincludes the architecture, tools, databases, applications, and thebusiness performance management methodology and it can leadto make better decisions.

Dependent variable

• Strategic decision-making: organizational strategic decisionsare decisions that are taken for prolonged periods and are lessfrequent, but are associated with high volumes of data andprocesses. Decisions made in these levels are often in the field

of unstructured issues and are made by senior managers and theresults have long-term effects in the path of organization.

Mediator variable: These variables affect the relationshipbetween the dependent and independent variables.

• Quality: A decision has quality when it makes more utilityand increases the satisfaction of all stakeholders.

• Flexibility: Flexible decisions adapt themselves to theenvironment and they are in harmony with other decisions inorganization.

• Agility: Agility of a decision means to make decisions withmore speed and accuracy.

• Integration: Integrated decisions, using shared resources,reduce complexity and make it easier to reach goals.

• Efficiency: Efficient decisions shorten the process of decision-making and reduce costs of decision-making.

Quality

Agility

Flexibility

Integration

Effectiveness

Efficiency

BusinessIntelligence

Strategic DecisionMaking

H1

H2

H3

H4

H5

H6

H7



• Effectiveness: The effective decisions lead to optimality indecision-making and accomplish goals (Zaman, 2005).

4.1 Reliability and validity of the questionnaire

The purpose of the reliability is that the device can measure thedesired properties and characteristics (Khaki, 1382). Reliabilityis a term that refers to accomplish the desired goals (Azar,2009). In reliability test, the purpose is to understand thepotential problems and ambiguities in the questions andstructure of the questionnaire and etc. First, to examine theformal reliability of questionnaire and accuracy of the questions,the questionnaire was distributed among a number of experts

and then the questionnaires were distributed among thepopulation of the research (Iran Scientific Association of E-commerce and the Undersecretary of Technology in Ministry ofIndustry, Mine and Trade). Validity shows logical stability andharmony of responses in measurement tools and helps to assessthe accuracy and quality of measurement tools (Azar, 2009). Inthis survey, validity or reliability of questionnaire wascalculated using the method of Cronbach’s Alpha. Usually, therange of reliability coefficient of Cronbach’s Alpha is from zero,which means lack of stability, to one, which means full validity.When the number becomes nearer to one, the reliability ofquestionnaire will be raised. SPSS software is used to calculatethe Cronbach’s Alpha, and the reliability of questionnaire for acase of 20 ones was assessed as 0.889 that admits the validity ofthe questionnaire (Table 3).

Table (3). The Statistics of Research Reliability

Reliability StatisticsCronbach's

Alpha N of Items0.889 28

Based on the aim of the present study, it is an applied research,because the subject is dealt with in a particular organization.Also, this study has been conducted through the correlationmethod, since in correlation method, the main aim is to specifythe relationship of two or more variable and, if so, its amountand intensity (Khaki, 2004). Regarding the subject of the studywhich is analysis of the effect of business intelligence onstrategic organizational decisions, the population of the researchis consisted of the experts of the scientific society of E-commerce of Iran and the undersecretary of technology in theministry of industry, mine and trade. The number of thepopulation is 650. In this study, the simple random samplingmethod was used. Also, the Cochran formula was used todetermine the sample size and the sample size was estimated242. Based on the research model in this study, the assumptionswhich are raised in this study are as follows:

Business intelligence is effective in improving thequality of strategic decisions.

Business intelligence leads to agility of strategicdecisions.

Business intelligence leads to flexibility of strategicdecisions.

Business intelligence leads to integration of strategicdecisions.

Business intelligence leads to improve strategicdecision-making effectiveness.

Business intelligence leads to improve the efficiency ofstrategic decisions.

Business intelligence leads to improve strategicdecisions.

5. Results

The results of the study are presented in two parts of descriptivestatistics and inferential statistics. The descriptive statistics partstudies the population in terms of frequency, mean and standarddeviation. Inferential statistics analyzes the results usingcorrelation, factor analysis and structural equations. Factoranalysis examines admittance or rejection of components of themodel. Correlation analysis examines the relationship ofvariables of the model and its intensity. Structural equationsanalyze the relationship of the components and the generalstructure of the model and goodness of fit in the model in twomodes of standard mode and meaningful mode. The summary ofthe results is presented in the following part:

5-1. Summary of the results of descriptive statistics ofdemographic data

In this study, 242 samples were assessed that their demographicinformation is provided in the table below.

Table (4). Summary of the results of descriptive statistics of demographic data

Variable Frequency Percentage

Gender MaleFemale

14795

60.739.3

Age 21 to 2526 to 30

30 and above

1016270

4.166.928.9

Level of education BachelorsMasters

PhD.

7114031

29.357.912.8



5-2. Summary of the results of descriptive statistics of theresearch variables

The following table summarizes the results of the descriptivestatistics for the study variables.

Table (5). Results of the descriptive statistics for research variables

StandardDeviation

MeanNumber ofQuestions

Variable

1.443.023Integration1.032.902Flexibility

1.432.343Agility1.402.872Quality1.293.502Effectiveness1.103.642Efficiency1.902.986Business Intelligence1.413.226Strategic Decision-

making

5-3. Summary of the results of inferential statistics

Inferential statistics in this study will be presented in threesections: Correlation analysis and the measurement model(confirmatory factor analysis), components and variables of theresearch (for reliability analysis) and structural equationsmodeling (measuring the effect of variables on each other). Thefollowing table shows a summary of the results of researchmeasurement model (Mirzaei, 2009).

Factor analysis can have two forms of exploratory andconfirmatory. Based on the aim of data analysis we can decideon one of these two methods to be used in factor analysis.

In exploratory analysis, the researcher is looking for analyzingthe experimental data in order to discover and identify theindexes and their relationships. In other words, the exploratoryanalysis has proposed and surveillance value and also it can

make structures, models or assumptions. Exploratory factoranalysis is a method often used to detect and measure theobserved variables. Researchers have recognized the fact thatexploratory factor analysis can be quite useful in the early stagesof testing experience or education.

On the other hand, most of studies may be partly exploratoryand partly confirmatory, because they include both knownvariables and unknown variables. Known variables must bechosen carefully in order to provide further information aboutthe unknown variables as much as possible. It is desirable toconfirm or reject the hypothesis discovered by exploratoryanalysis through statistical methods. Exploratory analysisrequires large-volume samples. In this study, the results ofexploratory factor analysis using SPSS software andconfirmatory factor analysis using LISREL software arepresented. It should be noted that in order to reduce the variablesand consider them as latent variables, the factor must be greaterthan 0/3. Exploratory factor analysis results are shown in thetable below (Mirzaei, 2009).

Table (6). Summary of the results of the exploratory factor analysis

Questions Aspect Variables FactorialLoad

Result

1 Efficiency Cost 0/621 The questions assess the variable Correctly.2 Process 0/761 The questions assess the variable Correctly.3 Effectiveness Achieving Goals 0/630 The questions assess the variable Correctly.4 Optimality 0/596 The questions assess the variable Correctly.5 Quality Desirability 0/501 The questions assess the variable Correctly.6 Satisfaction 0/698 The questions assess the variable Correctly.7 Speed 0/714 The questions assess the variable Correctly.8 Agility Accuracy 0/643 The questions assess the variable Correctly.9 Correctness 0/668 The questions assess the variable Correctly.10 Flexibility Harmony 0/721 The questions assess the variable Correctly.11 Adjustment 0/537 The questions assess the variable Correctly.12 Integrity Sources 0/730 The questions assess the variable Correctly.13 Complexity 0/602 The questions assess the variable Correctly.14 Availability 0/584 The questions assess the variable Correctly.15 Efficiency 0/565 The questions assess the variable Correctly.



16 Effectiveness 0/587 The questions assess the variable Correctly.17 Business

IntelligenceQuality

0/711The questions assess the variable Correctly.

18 Agility 0/866 The questions assess the variable Correctly.19 Flexibility 0/711 The questions assess the variable Correctly.20 Integrity 0/850 The questions assess the variable Correctly.21 Efficiency 0/612 The questions assess the variable Correctly.22 Effectiveness 0/766 The questions assess the variable Correctly.23 Quality 0/669 The questions assess the variable Correctly.24 Strategic

Decision-making

Agility0/516

The questions assess the variable Correctly.

25 Flexibility 0/775 The questions assess the variable Correctly.26 Integrity 0/575 The questions assess the variable Correctly.

In confirmatory factor analysis, researchers seek to develop amodel that is supposed to describe, explain or justify theexperimental data based on a relatively small number ofparameters. This model is based on empirical information aboutthe data structure that can be formed as: 1) a theory orhypothesis, 2) a certain scheme for the classification of items in

accordance with the actual characteristics of form and content,3) known empirical conditions or 4) the knowledge gained fromprevious studies about the large data. Factor analysis can becalculated through SPSS and LISREL software which differslightly (Mirzaei, 2009).

The following table shows the results of confirmation orrejection of a relationship between variables of the research:

Table (7). Summary of the results of the confirmatory factor analysis

Hidden Variable Revealed Variable Standard FactorialLoad

T-Value FactorialLoad

Result

Efficiency Cost 0/43 2/87 Relationship ConfirmedEfficiency Process 0/59 5/80 Relationship Confirmed

Effectiveness Achievement ofGoals

0/48 3/99Relationship Confirmed

Effectiveness Optimality 0/41 3/04 Relationship ConfirmedQuality Desirability 0/76 4/87 Relationship ConfirmedQuality Satisfaction 0/86 8/93 Relationship ConfirmedAgility Speed 0/56 6/87 Relationship ConfirmedAgility Accuracy 0/55 7/87 Relationship ConfirmedAgility Correctness 0/87 6/94 Relationship Confirmed

Flexibility Harmony 0/75 2/87 Relationship ConfirmedFlexibility Adjustment 0/43 5/80 Relationship ConfirmedIntegrity Sources 0/46 4/98 Relationship ConfirmedIntegrity Complexity 0/76 5/23 Relationship ConfirmedIntegrity Availability 0/65 6/29 Relationship ConfirmedBusiness

IntelligenceEfficiency



Effectiveness0/57 4/57

Relationship Confirmed


Quality0/49 4/19



Agility0/32 6/62



Flexibility0/41 6/82



Integrity0/43 7/81


StrategicDecision-making

Efficiency0/39 2/43



Effectiveness0/61 3/54


Strategic Quality 0/44 4/33 Relationship Confirmed



Decision-makingStrategic

Decision-makingAgility



Flexibility0/54 4/93



Integrity0/45 4/90


One of the new methods of reviewing causal relationshipsbetween variables is structural equations method. The analyzedassumption in a structural equations model is a causal structureamong a set of structures that are not visible. These structuresare measured through a set of observation variables (Sarmad,Bazargan and Hejazi, 2007).

The following figures show the numbers of meaningfulness andstandardized estimation of structural equations modeling. As itis evident, LISREL software presents a series of indexes tomeasure the goodness of fit in the developed model. Theindexes for the conceptual model are as follows:

Chi-square index (χ2): It indicates the chi-square statistic forthe model. In fact, the index represents the difference between

the model and the data and it is a measure for badness of themodel. So, when it is less, the difference between the variance-covariance matrix of the sample taken and the variance-covariance resulted from the sample taken and it shows that themodel is bad. It should be noted that this index is influenced bythe taken sample. In fact, when the sample size is greater than200, the index has a strong tendency to increase. Therefore,analyzing the fitness of the model through this index is typicallyreliable in samples between 100 and 200. Also, it is better tointerpret the index with consideration of degrees of freedom.

Degrees of freedom (df): This index indicates the degree offreedom in a model and it should not be less than zero.

P-Value Index: This indicator is also another criterion forassessing the suitability of the model. But there is no consensusabout the credibility of this index. Some scholars believe that itsamount should be less than 0.05, while some insist on a higheramount.

Mean Square of Errors in the Model (RMSEA): This index ismade based on the model errors and like the chi-square index isa measure for badness of model. Some scholars believe that thisindex should be less than 0.05, while others believe that itshould be less than 0.08.

Estimation of the range of RMSEA in the confidence level of90%: The LISREL software estimates a confidence interval forthe mean square of errors in the model.

Goodness-of-Fit Index (GFI): This index is a measure formeasuring goodness of the model and an amount higher than0.9, indicates the suitability of the model extracted from thedata.

Adjusted GFI (AGFI): This index is in fact the adjusted formof GFI index, considering the degrees of freedom (df), and it isanother criterion for a good model. If the level of the index ishigher than 0.9, it indicates the suitability of the modelregarding the data.

Normed Fit Index (NFI): This index is another indicator tomeasure the quality of a model according to the data. If the levelof the index is higher than 0.9, it indicates the suitability of thederived model.

In the following figure, the final model of the research is shownin two modes of the standardized mode and the number ofmeaningfulness (mode t-value), and also the results of thestructural equations model has been summarized for hypotheses.

As the path analysis results show, business intelligence has adirect and positive impact on efficiency (r = 0.34, t = 6.78). Thedata analysis results show that the business intelligence has adirect and positive impact on effectiveness (r = 0.45, t = 9.43).Also, business intelligence has a significant direct effect on thequality (r = 0.46, t = 7.33). The results of the analysis betweenbusiness intelligence and agility shows that this effect issignificant (r = 0.34, t = 9.42). The results also show the effectof business intelligence on flexibility (r = 0.43, t = 8.32) andbusiness intelligence on integration (r = 0.63, t = 10.32) issignificant.

Efficiency has a direct impact on strategic decisions (r = 0.43, t= 7.63). Also, effectiveness has a direct impact on strategicdecisions (r = 0.47, t = 6.37). Analytical results between twovariables of quality and strategic decisions show that the impactis not positive and significant and no correlation has beenobserved between quality and strategic decisions (r = 0.21, t =1.22). The results also show the impact of agility on strategicdecisions (r = 0.38, t = 8.31) and the impact of flexibility onstrategic decisions (r = 0.55, t = 10.51) are significant. Structuralequations modeling results indicate that the integrity has a directpositive impact on strategic decisions (r = 0.58, t = 11.30).



Table (8) Summary of the Results of structural equations modeling

Confirmation orRejection of the

Hypothesis

Numbers ofSignificance

(t-value)

The Ratio ofInfluence in

Standard Mode

Direct Effect

Confirmed6.78 0.34

The Effect of Business Intelligenceon the Efficiency of Strategic

DecisionsConfirmed

9.43 0.45The Effect of Business Intelligence

on the Effectiveness of StrategicDecisions

Rejected1.22 0.21

The Effect of Business Intelligenceon the Quality of Strategic Decisions

Confirmed9.42 0.34

The Effect of Business Intelligenceon the Agility of Strategic Decisions

Confirmed8.31 0.43

The Effect of Business Intelligenceon the Flexibility of Strategic

DecisionsConfirmed

10.32 0.63The Effect of Business Intelligence

on the Integrity of StrategicDecisions

Confirmed9.83 0.56

The Effect of Business Intelligenceon the Improvement of Strategic

Decisionsχ2 = 77.54, Df = 27, P-Value = 0.00162, RMSEA = 0.063, GFI= 0.902, AGFI= 0.939,NFI= 0.959

Results of structural equations analysis show that all of thehypotheses are supported. Only the effect of business

intelligence on quality of strategic decisions has been rejected.The final model of results is shown in the following figure.

Fig (3). The ultimate model of research

6. Conclusion

Making decisions that are in consistent with the goals of theorganization is possible just when you have correct information.The aim of business intelligence is to provide access to usefulinformation, at the right time, to help make better decisions.Organizational readiness is an important factor for decisionmaking regarding the using or not using the businessintelligence. Business intelligence is designed to help extract theuseful information from the data gathered by software systems.In this study, we sought to examine the effect of BI on an

organization’s strategic decisions. In order to analyze the effectof business intelligence on strategic decisions, the pressure-response-support model in business was used. Considering therequirements of the study, the conceptual model of the researchwas designed. The components of the model which evaluate theeffect of business intelligence on strategic decisions are 6components which are as follows: Efficiency, Effectiveness,Quality, Flexibility, Consistency and Agility.

In order to evaluate the model, a questionnaire was designed andit was distributed among the members of the undersecretary oftechnology in the ministry of industry, mine and trade, and thescientific association of e-commerce that are familiar with the



business intelligence project and such projects, and the resultswere analyzed.

BI application in strategic level can be considered to helpincrease the overall efficiency and process optimization inorganizations. These systems focus on some important financialfeatures and other important parameters in increasing theefficiency of the organization. It is evident that the system inthese levels should also encompass the external processes oforganization.

Business Intelligence, through its influence on the dimensions ofdecision including efficiency, effectiveness, agility, flexibilityand integrity, improves the organizational strategic decisions.

This study includes 7 hypotheses that after analyzing, sixhypotheses were confirmed and only one hypothesis wasrejected. Based on the hypotheses of the study, the followingsuggestions are recommended to managers to develop the use ofbusiness intelligence to make strategic decisions:

First hypothesis: BI is effective in improving the quality ofstrategic decisions.

Quality of strategic decisions is monitored through the variablesof desirability and satisfaction. Based on the results of factoranalysis, these two variables measure the quality of decisionmaking well, but the effect of business intelligence onimproving the quality of strategic decisions is rejected.Therefore the following suggestions are recommended:

1. Training courses to be held for senior executives and otheremployees about BI concepts.

2. Using tools of customer relationship management, datamining and online analytical processing in order to improve thequality of strategic decisions.

Second hypothesis: BI leads to Agility in strategic decisions.

The agility of strategic decisions can be monitored through threevariables of speed, accuracy and precision. Based on the resultsof factor analysis, these variables evaluate the agility of thedecisions well. The effect of business intelligence onimprovement of agility in strategic decisions has been approved.Therefore the following suggestions are recommended:

1. The pervasive use of BI in the organization in order tooptimize decisions at the executive and operational levels.

2. Using the tools of data storage and online analysis database inorder to increase the agility of organizational decisions.

The third hypothesis: BI leads to flexible strategic decisions.

Flexibility of strategic decisions can be monitored through twovariables of harmony and adjustment. Based on the results offactor analysis, these variables measure the flexibility ofdecision making well. The effect of business intelligence onimprovement of the flexibility of strategic decisions is approved.Therefore the following suggestions are recommended:

1. Utilizing the balanced scorecard to enhance organizationalflexibility.

2. Using the tools of data analysis and text analysis of businessintelligence in order to identify challenges and opportunities,and to be adjusted to the environmental changes.

Hypothesis IV: Business intelligence leads to the integrationof strategic decisions.

Integration of strategic decisions is monitored through threevariables of common sources, complexity and availability.Based on the results of factor analysis, these variables canmeasure the integrity of the decision making well. The effect ofbusiness intelligence on the improvement of integration instrategic decisions is approved. Therefore the followingsuggestions are recommended:

1. The use of enterprise resource planning systems (ERP) inorder to develop the organizational integrity.

Hypothesis V: BI can improve the effectiveness of strategicdecisions.

Effectiveness of strategic decisions can be monitored throughtwo variables of achieving the purposes and optimality. Basedon the results of factor analysis, these variables can measure theeffectiveness of decisions well. The effect of businessintelligence on improvement of the effectiveness of strategicdecisions has been approved. Therefore the followingsuggestions are recommended:

1. Analyzing the organizational position and using some of therequired tools needed, regarding the organizational priorities andneeds.

2. Continuous monitoring of objectives and making intelligentdecisions in order to work in harmony with organizational goalsand strategies.

Hypothesis VI: Business Intelligence can improve theefficiency of strategic decisions.

The efficiency of strategic decisions can be monitored throughtwo variables of realization of the cost and the process. Based onthe results of factor analysis, these variables measure theefficiency of decision making well. The effect of businessintelligence on improving the efficiency of strategic decisionshas been confirmed. Therefore the following suggestions arerecommended:

1. Cost-Benefit Analysis of Business Intelligence Systems in anorganization.

2. Reengineering business processes to improve organizationalprocesses.

3. Identify the key factors of success in implementation ofbusiness intelligence in organization.

Hypothesis VII: Business intelligence can improve thestrategic decisions.

Business Intelligence can improve strategic decision makingthrough affecting the efficiency, effectiveness, flexibility,agility, quality and integrity of decision making. The results of



factor analysis and structural equations illustrate this issue.Therefore the following suggestions are recommended:

1. Using business intelligence approach to make organizationalstrategic decisions.

2. BI application development in order to improve the decision-making continuously.

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