Description
Measuring The Imapct Of Business Intellegence On Performance: An Empirical Study
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MEASURING THE IMAPCT OF BUSINESS INTELLEGENCE
ON PERFORMANCE: AN EMPIRICAL STUDY
AL-Shubiri F.
?
Abstract: In this study explain rapidly changing business environment, the need for very
timely and effective business information is recognized as being indispensable for
organizations not only to succeed, but even to survive. Business intelligence (BI) is a
concept which refers to a managerial philosophy and a tool that is used in order to help
organizations and refine information and to make more effective business decisions. The
sample of study is 50 industrial firms for the period 2006-2010 listed on Amman Stock
Exchange .The results indicates the Knowledge economy variable measured by intellectual
capital are more significant and effect of performance and this study has shown that the
provision of appropriate support with regard to BI is needed as BI plays a crucial role to
support decision-making in firms of all sizes more than learning and growth or financial
factor but there is no significant level for customer variable
Keywords: Business intelligence, Intellectual capital, Performance
Introduction
The participation of firms in the knowledge economy is important not only for their
own competitive advantage in the marketplace but also for the competitiveness of
their country as a whole. Business intelligence systems combine operational data
with analytical tools to present complex and competitive information to planners
and decision makers. The objective is to improve the timeliness and quality of
inputs to the decision process. Business Intelligence is used to understand the
capabilities available in the firm; the state of the art, trends, and future directions in
the markets, the technologies, and the regulatory environment in which the firm
competes; and the actions of competitors and the implications of these actions.
The BI terminology in recent years has been con-fusing. There are different
interpretations of BI and many terms applied to it (e.g. competitive intelligence,
market intelligence, customer intelligence, competitor intelligence and strategic
intelligence). The use of these terms is haphazard both in academia and the
business world. After all, almost all the definitions share the same referent even if
the term has been defined from several perspectives [4] and they all include the
idea of analysis of data and information. The main idea in BI is to aid in controlling
the vast stocks and flow of business information around then processing the
information into condensed and useful managerial knowledge and intelligence.
The task described includes nothing too new and it responds to old managerial
problems. For example, [6] have stated that organizations have ‘collected
information about their competitors since the dawn of capital-ism. The real
?
Faris Nasif AL- Shubiri PhD., Assistant professor , Amman Arab University –Jordan ,
Faculty of Business , Department of Finance and Banking,
? corresponding author: [email protected]
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revolution is in the efforts to institutionalize intelligence activities.’ Thus, it is
likely that all organizations have some kind of BI activities or similar activities.
There are some questions to know BI as following: Business Intelligence is used to
understand the capabilities available in the firm: the state of the art, trends, and
future directions in the markets, the technologies, and the regulatory environment
in which the firm competes; and the actions of competitors and the implications of
these actions.
Business Intelligence systems present complex corporate and competitive
information to planners and decision makers. The objective is to improve the
timeliness and quality of the input to the decision process. Business intelligence is
a form of knowledge. The techniques used in knowledge management for
generating and transferring knowledge, [7] apply. Some knowledge is bought (e.g.,
scanner data in the food industry) while other knowledge is created by analysis of
internal and public data. Knowledge transfer often involves disseminating
intelligence information to many people in the firm. For example, salespeople need
to know market conditions, competitor offerings, and special offerings. Business
intelligence (BI) is the most recent development of systems that support
organizational decision-making. For example, an owner-manager may want to
know not only the revenue generated per client but also how profitable each client
is to decide which clients to target for future sales and marketing efforts.
Business intelligence is a natural outgrowth of a series of previous systems
designed to support decision making. The emergence of the data warehouse as a
repository, the advances in data cleansing that lead to a single truth, the greater
capabilities of hardware and software, and the boom of Internet technologies that
provided the prevalent user interface all combine to create a richer business
intelligence environment than was available previously. Business intelligence is
used by decision makers throughout the firm. At senior managerial levels, it is the
input to strategic and tactical decisions. At lower managerial levels, it helps
individuals to do their day-to-day job. In some firms, business intelligence
capabilities are rolled out to most of its professionals (i.e., ‘BI for the masses’).
The advent of the “knowledge economy” has engendered a great deal of interest in
how intangible knowledge assets or intellectual capital (IC) are managed in
organizations. The implicit or explicit assumption in both practical and scholarly
work is that better management of IC will lead to unique, sustainable competitive
advantage. Consequently, a great deal of time and effort have been expended on
measuring IC, on developing systems and tools to manage it, and, to a more limited
extent, estimating the impact of IC on performance. IC management is, of course, a
variation on the concept of knowledge management. We choose to use the former
term in this article given our emphasis on financial data and measurement of
knowledge assets. Most of the technologies needed for business intelligence serve
multiple purposes. For example, the World Wide Web is used for both knowledge
generation and knowledge transfer. However, specialized software for doing
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analysis is the heart of business intelligence. This software is an outgrowth of the
software used for decision support and executive information systems in the past.
The economic landscape in Jordan has changed dramatically in recent years: from a
buoyant economic climate with an abundant availability of credit with relatively
reliable and stable power supply, firms now find themselves challenged in ways
they had never expected. Growth firms face obstacles such as tighter budgets,
reduced access to credit, and a technology landscape more complex than ever.
Organizations must be flexible and quick to respond to constantly changing
business conditions. To do so, timely intelligence about the organization, its
processes, and its business partners must be available to inform decisions and
actions to achieve or maintain a competitive advantage in the marketplace.
Systems that support decision-making in organizations are therefore an important
component in organizational information dissemination and have the potential to
impact positively on performance and competitiveness. Making informed decisions
is important for any organization, but is especially crucial for firms as valuable
time and money cannot be wasted on incorrect decisions when economic belts are
already tightened.
The purpose of this study was therefore to engage with firms in Jordan to explore
the use of BI in their enterprises in order to provide insight into the situation with
regard to BI in firms of Jordan. The research objectives were to understand how
information is used in firms; if BI is used, to describe BI in the context of firms or
if it is not used, to determine why not; and to indicate the implications of the
research results and to suggest future research
Theoretical framework
Business Intelligence:
[23] remarks that definitions of BI vary depending on the perspective from which it
is defined .In most organizations BI capabilities, once adopted, evolve from simple
standard reports and queries showing what happened to more advanced analytics
such as multi-dimensional analysis that examine why it happened to data mining
that predicts what might happen in future [24]. The systems/technology used to
support decision-making can either be informal or formal. Spreadsheets represent
the simplest form of decision support and are often found in both SMEs [16] and
large organizations alike across the analytical spectrum [14; 20].
While the term Business Intelligence is relatively new, computer-based business
intelligence systems appeared, in one guise or other, close to forty years ago. BI as
a term replaced decision support, executive information systems, and management
information systems, [27]. With each new iteration, capabilities increased as
enterprises grew ever-more sophisticated in their computational and analytical
needs and as computer hardware and software matured.
BI systems are defined as follows:
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BI systems combine data gathering, data storage, and knowledge management with
analytical tools to present complex internal and competitive information to
planners and decision makers.
Implicit in this definition is the idea (perhaps the ideal) that business intelligence
systems provide actionable information delivered at the right time, at the right
location, and in the right form to assist decision makers. The objective is to
improve the timeliness and quality of inputs to the decision process, hence
facilitating managerial work.
Sometimes business intelligence refers to on-line decision making, that is, instant
response. Most of the time, it refers to shrinking the time frame so that the
intelligence is still useful to the decision maker when the decision time comes. In
all cases, use of business intelligence is viewed as being proactive. Essential
components of proactive BI are, [15]:Real-time data warehousing, • Data mining, •
Automated anomaly and exception detection, • Proactive alerting with automatic
recipient determination, • Seamless follow-through workflow, • Automatic learning
and refinement, • Geographic information systems • Data visualization
What Does BI Do?
BI assists in strategic and operational decision making. A Gartner survey ranked
the strategic use of BI in the following order, [29]:
1. Corporate performance management
2. Optimizing customer relations, monitoring business activity, and traditional
decision support
3. Packaged standalone BI applications for specific operations or strategies
4. Management reporting of business intelligence
One implication of this ranking is that merely reporting the performance of a firm
and its competitors, which is the strength of many existing software packages, is
not enough. A second implication is that too many firms still view business
intelligence (like DSS and EIS before it) as an inward looking function.
David Packard from Hewlett-Packard, who once said that marketing is too
important to be left to the organizational unit (sector/service/department) for
marketing and need to successful organizations. Consequently, these organizations
have accepted the thesis that creating, communicating and delivering value to
consumers, is not the responsibility of the personnel of the marketing
organizational unit only, but of all other employees as well (organizational units of
production, R&D, Accounting, Finance, HR Human Resource, IT Information
Technologies, etc..). [11].
Business intelligence is a natural outgrowth of a series of previous systems
designed to support decision making. The emergence of the data warehouse as a
repository, the advances in data cleansing that lead to a single truth, the greater
capabilities of hardware and software, and the boom of Internet technologies that
provided the prevalent user interface all combine to create a richer business
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intelligence environment than was available previously. BI pulls information from
many other systems.
Competitive Intelligence Analysis:
Next to knowing all about your own business, the best thing to know about is the
other fellow’s business.” John D. Rockefeller [2] Competitive intelligence (CI) is a
specialized branch of Business Intelligence. It is “no more sinister than keeping
your eye on the other guy albeit secretly” [12]. Competitive Intelligence is a
systematic and ethical program for gathering, analyzing and managing external
information that can affect your company’s plans, decisions and operations. In
other words, CI is the process of ensuring your competitiveness in the marketplace
through a greater understanding of your competitors and the overall competitive
environment. “You can use whatever you find in the public domain to ensure that
you will not be surprised by your competitors.” [12]. CI is not as difficult as it
sounds. Much of what is obtained comes from sources available to everyone,
including [12]:
• Government websites and reports • Online databases, interviews or surveys, •
Special interest groups (such as academics, trade associations, and consumer
groups), • Private sector sources (such as competitors, suppliers, distributors,
customer) or • Media (journals, wire services, newspapers, and financial reports).
The challenge with CI is not the lack of information, but the ability to differentiate
useful CI from chatter or even disinformation.
Of course, once a firm starts practicing competitive intelligence, the next stage is to
introduce countermeasures to protect itself from the CI of competitor firms. The
game of measure, countermeasure, and counter-countermeasure, and so on to
counter to the nth measure is played in industry just as it is in politics and in
international competition.
Literature Review
The core of business intelligence is the collective sense-making. In literature,
sense-making has been defined in different ways. It is an interpretative process
where people assign meaning to ongoing events [10]. It is the amplification of
weak signals and the search for contexts within small details fitted together for
sense-making [26]. It is considered as a creative and collective method that can
help the organization to give sense and see possibilities in the surrounding disorder
[3; 1]. [5] A positive aspect of subjective measurements is that the results show
how effective the users consider the intelligence products. However, subjective
measurements do not establish any monetary value for the effects of BI. [17]
Proposed a model referred to as VAS-IC (a French formulation of Anticipative
Strategic Environmental Scanning-Collective Intelligence) with a core process of
collective sense-making. The main steps of VAS-IC are described in figure 1
below [19], the organizations inter-viewed compare the cost of consultants to the
results obtained by the CI division and quantify the strategic deals that the CI team
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has been involved in and then compare the win / loss ratios to those deals where
they were not involved [16], the ?size-adjusted expenditure on items likely to
yield primarily long-term returns, is lower amongst small than large firms. SMEs
are slow to exploit opportunities offered by new technology to support their
growth. The ICT adoption behavior of SMEs is influenced by a range of factors
that can be ascribed to their unique characteristics [9] chief amongst these being
their limited resources, financial and otherwise This is reiterated by [22] stating
that the majority of the world‘s emerging economies indicate that micro, small and
medium enterprises will be the predominant enterprise for the foreseeable future as
these enterprises play a key role in economic growth and development. According
to [26] it is ?essential for small businesses in today‘s competitive environment to
take a strategic approach to their information needs if they wish to develop and
remain competitive.In a preliminary study, the basic idea is the following
Main Hypothesis 1: There is no impact of intelligence business on performance of
industrial firms
Hypothesis 1-1: There is no impact of Learning and growth Variable on
performance of industrial firms
Hypothesis 1-2: There is no impact of Financial Variable on performance of
industrial firms
Hypothesis 1-3: There is no impact of Customer Variable on performance of
industrial firms
Hypothesis 1-4: There is no impact of Knowledge economy variable on
performance of industrial firms
Methodology:
The sample of study is 50 industrial firms for the period 2006-2010 listed on
Amman Stock Exchange
The Model of Study:
The business intelligence for independent variable and this variable consist many
factors for how to measured .[5] has developed a measurement model called CI
Measurement Model (CIMM), which can be used to calculate the return on CI
investment (ROCII). Indeed, the resource-based theory of the firm reinforced the
idea that competitive advantage flows from unique resources of the organization
eventually leading to sustainable core competencies [25]. As capital and basic labor
became readily available to most organizations of any size, scholars began looking
for other factors that might explain why one firm is successful and another is not.
Parts of the discussion focused on intangibles, and we're all familiar with concepts
such as goodwill and brand equity, so the idea that intangible assets have value is
also nothing new. Indeed, the Tobin's Q measure of intangibles (market value to
replacement cost of assets) goes back decades. Newer measures developed during
the 1990's include the Balanced Scorecard [13].
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Independent Variables
Learning and growth Variable measured by: Administrative expenses per customer
(AE/C)Innovation: contribution to constant innovation is to be considered a task as
well as responsibility of the intellectual worker; it is part of his job. Learning and
teaching: intellectual work requires continuous self-learning as well as an
engagement to teach others and transfer knowledge [18].
Financial Variable measured by: return on investment (ROI)
Customer Variable measured by: Number of customer complaints (NCC)
From an economic point of view, unemployment is regarded as an expression of
several imbalances on the labor market that appears when the labor force offer
exceeds the demand, and on the market of goods and services the unemployment
appears when production exceeds demand. Therefore, the unemployment forms on
the basis of two processes: loosing the job by one part of the active population and
the increase of the job offer by reaching the legal age for work of new generations
[21].
Knowledge economy variable has engendered a great deal of interest in how
intangible knowledge assets or intellectual capital (IC) are managed in
organizations measured by: market value less book value (MV-LV).The concept
of the „knowledge worker” defines with reference to the context of post-industrial
transformation (new economy, information/ network/ knowledge/ learning
economy/ society. It is a conceptual reflection upon the complex and underlying
developments which evolved in the most advanced economies (with particular
respect to Japan and the USA). Peter F. Drucker is the first whose early assertions
with regards highly qualified intellectual labour have grown to meet the definition
criteria that is in use today to describe knowledge workers [18].
Dependent variable measured by: return on equity (ROE) as performance
indicator. The equation for Business performance was expressed in the following
equation
Performance (ROE) =a +?
1
AE/C+?
2
ROI +?
3
NCC+ ?
4
MV-BV+e
it
----Model (1)
Correlation Analysis:
A correlation coefficient measured the strength of a linear between the four
variables of A correlation Coefficient measured the strength of a linear between
two variables. The correlation results were shown in the Table (1).
Table 1. Pearson Correlation between variables BI and performance
Ind.
Variables
AE/C ROI NCC MV-BV
Person
Correlation
0.290* 0.327** 0.213 0.499***
Sig – 2
Tailed
0.065 0.042 0.112 0.001
Note: Asterisks (***) , (**) and (*) indicates significance at 1%,5% and 10%
respectively.
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This preliminary study suggests that a strong relationship may exist between
successful development of intellectual capital and organizational performance and
were significant at the 0.01 level .The correlations between AE/C, and Business
performance were positive and were significant at the 0.10 level, whereas
correlation between ROI and Business performance were positive and were
significant at the 0.05 level (2-tailed). Finally, no significant level between the
NCC and Business performance .Therefore, the study indicates that the correlations
between intellectual capital and Business performance were higher than others
variables.
Regression Analysis
In order to further reveal support for hypothesis 1, the factors that influenced
Business performance, the four variables of business intelligence process was used
in a multiple regression analysis. The regression procedure was employed because
it provided the most accurate interpretation of the independent variables.
Table 2. Regression Analysis Result
Ind.Variable
Const AE/C ROI NCC MV-BV
Dep. Var
ROE
3.886 2.994 3.121 2.417 5.194
0.031** 0.061* 0.041** 0.1119 0.0012***
St.co.beta ---- 0.310 0.390 0.190 0.480
VIF 1.081 1.441 1.418 1.484 1.145
Model -1- Model (1)
R
R
2
D-Watson
F-Statistic
Prob(F)
0.4462
0.214
5.954
14.158
0 .025
Note: Asterisks (***), (**) and (*) indicates significance at 1%, 5% and 10%
respectively.
The four independent variables were expressed in terms of the business intelligence
factor. The significant factors that remained in the regression equation were shown
in order of importance based on the beta coefficients.
In this study I used measures its BI performance in various ways. Measurement is
used as a tool to develop and improve BI activities as well as to demonstrate its
usefulness. Performance measures are chosen based on literature review The
methodology section illustrates the chosen focus areas pertaining to BI
measurement and they have a direct affect on the four chosen measurement focus
areas; financial, , learning and growth , customer and Knowledge economy
variables.
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BI performance is measured by determining the individuals and system activities
involved. These activities can be measured by using quantitative, qualitative and
time-related indicators. Quantitative measurement involves both input and output
indicators. Qualitative indicators include, e.g., the satisfaction of information users
and systematic information gathering is a prerequisite for efficient measuring.
There are two main challenges in measuring the effects of BI. First, the BI process
produces information and knowledge, which have to be utilized before the effects
are seen. The effects, if they occur, are intangible by nature, e.g. improved
decision-making ability. It is difficult to quantify these intangible phenomena.
These intangible effects may eventually have financial consequences. However,
distinguishing between the specific benefits received due to BI and the
achievements of ordinary decision-making is challenging .Thus, the second key
challenge in measuring the effects of BI is to distinguish what part of a
phenomenon, say increased market share, results from increased knowledge
produced by BI and what is caused by some other factors.
Table (2) showed the results of the regression analysis. To predict the of the
regression model, the multiple correlation coefficient (R), coefficient of
determination (R
2
), and F ratio were examined. First, the R of independent
variables (four variables) on the dependent variable (performance of firms, or
ROE) is 0.446, which showed that the performance had positive and high overall
association with the four attributes. Second, the R
2
is 0.214, suggesting that more
than 20% of the variation of performance was explained by the four attributes.
Last, the F ratio, which explained whether the results of the regression model could
have occurred by chance, had a value of 14.158 (p =0.025) and was considered
significant.
In other words, at least one of the four attributes was important in contributing to
performance. In the regression analysis, the beta coefficients could be used to
explain the relative importance of the four attributes (independent variables) in
contributing to the variance in s performance (dependent variable).
As far as the relative importance of the four business intelligence attributes is
concerned, MV/BV has, B1=0.480, p=0.0012) carried the heaviest weight for
performance, This measure will tend to favor larger firms, who may have more
intangible assets because of sheer size, not because they are clearly better at
managing such assets. Followed by ROI, B3=0.390, p=0.041 and AE/C, B2=-
0.310, p=0.061. Measuring the learning and growth sector is the most challenging
part in the balanced measurement process. Because of its intangibility, it is
challenging to measure e.g. organizational learning or if BI has resulted in better
decision-making but there is no significant to NCC variable. In conclusion, three
from four dimensions are significant. Thus, the results of multiple regression
analysis agree hypothesis 1, that there is relationship between the selected Business
intelligence and Business performance.
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Summary
This study has explored the role of BI in industrial firms on Jordan knowledge-
based from the perspectives of the key decision-maker. This paper has focused on
outlining the importance of tacit economic knowledge for the business intelligence
process measured by intellectual capital in industrial firms as one perspective affect
of performance and learning and growth process , customer and finally financial
perspective .These all variable exploring the business intelligence factor. The main
purpose of BI at firms is to enhance decision-making and service efficiency. The
main targets include efficiency, reasonable coverage of BI and user satisfaction. BI
comprises both internal and external business information, market information and
analysis. In fact, the whole concept of BI deals with providing insightful
information related to various business activities. Thus, it would be surprising if the
managers responsible for BI were not interested in obtaining intelligence
concerning its own operations.
The results indicates the Knowledge economy variable measured by intellectual
capital are more significant and effect of performance and this study has shown
that the provision of appropriate support with regard to BI is needed as BI plays a
crucial role to support decision-making in firms of all sizes more than learning and
growth or financial factor but there is no significant level for customer variable.
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POMIAR WP?YWU ANALIZY DANYCH BIZNESOWYCH NA WYDAJNO??:
BADANIA EMPIRYCZNE
Streszczenie: W niniejszym badaniu autor wyja?nia szybko zmieniaj?ce si? warunki
prowadzenia dzia?alno?ci gospodarczej, okre?la potrzeb? terminowej i efektywnej
informacji biznesowej która jest niezb?dne organizacjom, nie tylko do osi?gni?cia sukcesu
ale tak?e dla ich przetrwania . Business Intelligence (BI) to koncepcja, która odnosi si? do
filozofii kierowniczej oraz narz?dzie, które jest u?ywane, aby pomóc organizacji i
udoskonalenia informacji i podejmowaniu trafnych decyzji biznesowych.
??????????????????
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doc_273508531.pdf
Measuring The Imapct Of Business Intellegence On Performance: An Empirical Study
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MEASURING THE IMAPCT OF BUSINESS INTELLEGENCE
ON PERFORMANCE: AN EMPIRICAL STUDY
AL-Shubiri F.
?
Abstract: In this study explain rapidly changing business environment, the need for very
timely and effective business information is recognized as being indispensable for
organizations not only to succeed, but even to survive. Business intelligence (BI) is a
concept which refers to a managerial philosophy and a tool that is used in order to help
organizations and refine information and to make more effective business decisions. The
sample of study is 50 industrial firms for the period 2006-2010 listed on Amman Stock
Exchange .The results indicates the Knowledge economy variable measured by intellectual
capital are more significant and effect of performance and this study has shown that the
provision of appropriate support with regard to BI is needed as BI plays a crucial role to
support decision-making in firms of all sizes more than learning and growth or financial
factor but there is no significant level for customer variable
Keywords: Business intelligence, Intellectual capital, Performance
Introduction
The participation of firms in the knowledge economy is important not only for their
own competitive advantage in the marketplace but also for the competitiveness of
their country as a whole. Business intelligence systems combine operational data
with analytical tools to present complex and competitive information to planners
and decision makers. The objective is to improve the timeliness and quality of
inputs to the decision process. Business Intelligence is used to understand the
capabilities available in the firm; the state of the art, trends, and future directions in
the markets, the technologies, and the regulatory environment in which the firm
competes; and the actions of competitors and the implications of these actions.
The BI terminology in recent years has been con-fusing. There are different
interpretations of BI and many terms applied to it (e.g. competitive intelligence,
market intelligence, customer intelligence, competitor intelligence and strategic
intelligence). The use of these terms is haphazard both in academia and the
business world. After all, almost all the definitions share the same referent even if
the term has been defined from several perspectives [4] and they all include the
idea of analysis of data and information. The main idea in BI is to aid in controlling
the vast stocks and flow of business information around then processing the
information into condensed and useful managerial knowledge and intelligence.
The task described includes nothing too new and it responds to old managerial
problems. For example, [6] have stated that organizations have ‘collected
information about their competitors since the dawn of capital-ism. The real
?
Faris Nasif AL- Shubiri PhD., Assistant professor , Amman Arab University –Jordan ,
Faculty of Business , Department of Finance and Banking,
? corresponding author: [email protected]
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revolution is in the efforts to institutionalize intelligence activities.’ Thus, it is
likely that all organizations have some kind of BI activities or similar activities.
There are some questions to know BI as following: Business Intelligence is used to
understand the capabilities available in the firm: the state of the art, trends, and
future directions in the markets, the technologies, and the regulatory environment
in which the firm competes; and the actions of competitors and the implications of
these actions.
Business Intelligence systems present complex corporate and competitive
information to planners and decision makers. The objective is to improve the
timeliness and quality of the input to the decision process. Business intelligence is
a form of knowledge. The techniques used in knowledge management for
generating and transferring knowledge, [7] apply. Some knowledge is bought (e.g.,
scanner data in the food industry) while other knowledge is created by analysis of
internal and public data. Knowledge transfer often involves disseminating
intelligence information to many people in the firm. For example, salespeople need
to know market conditions, competitor offerings, and special offerings. Business
intelligence (BI) is the most recent development of systems that support
organizational decision-making. For example, an owner-manager may want to
know not only the revenue generated per client but also how profitable each client
is to decide which clients to target for future sales and marketing efforts.
Business intelligence is a natural outgrowth of a series of previous systems
designed to support decision making. The emergence of the data warehouse as a
repository, the advances in data cleansing that lead to a single truth, the greater
capabilities of hardware and software, and the boom of Internet technologies that
provided the prevalent user interface all combine to create a richer business
intelligence environment than was available previously. Business intelligence is
used by decision makers throughout the firm. At senior managerial levels, it is the
input to strategic and tactical decisions. At lower managerial levels, it helps
individuals to do their day-to-day job. In some firms, business intelligence
capabilities are rolled out to most of its professionals (i.e., ‘BI for the masses’).
The advent of the “knowledge economy” has engendered a great deal of interest in
how intangible knowledge assets or intellectual capital (IC) are managed in
organizations. The implicit or explicit assumption in both practical and scholarly
work is that better management of IC will lead to unique, sustainable competitive
advantage. Consequently, a great deal of time and effort have been expended on
measuring IC, on developing systems and tools to manage it, and, to a more limited
extent, estimating the impact of IC on performance. IC management is, of course, a
variation on the concept of knowledge management. We choose to use the former
term in this article given our emphasis on financial data and measurement of
knowledge assets. Most of the technologies needed for business intelligence serve
multiple purposes. For example, the World Wide Web is used for both knowledge
generation and knowledge transfer. However, specialized software for doing
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analysis is the heart of business intelligence. This software is an outgrowth of the
software used for decision support and executive information systems in the past.
The economic landscape in Jordan has changed dramatically in recent years: from a
buoyant economic climate with an abundant availability of credit with relatively
reliable and stable power supply, firms now find themselves challenged in ways
they had never expected. Growth firms face obstacles such as tighter budgets,
reduced access to credit, and a technology landscape more complex than ever.
Organizations must be flexible and quick to respond to constantly changing
business conditions. To do so, timely intelligence about the organization, its
processes, and its business partners must be available to inform decisions and
actions to achieve or maintain a competitive advantage in the marketplace.
Systems that support decision-making in organizations are therefore an important
component in organizational information dissemination and have the potential to
impact positively on performance and competitiveness. Making informed decisions
is important for any organization, but is especially crucial for firms as valuable
time and money cannot be wasted on incorrect decisions when economic belts are
already tightened.
The purpose of this study was therefore to engage with firms in Jordan to explore
the use of BI in their enterprises in order to provide insight into the situation with
regard to BI in firms of Jordan. The research objectives were to understand how
information is used in firms; if BI is used, to describe BI in the context of firms or
if it is not used, to determine why not; and to indicate the implications of the
research results and to suggest future research
Theoretical framework
Business Intelligence:
[23] remarks that definitions of BI vary depending on the perspective from which it
is defined .In most organizations BI capabilities, once adopted, evolve from simple
standard reports and queries showing what happened to more advanced analytics
such as multi-dimensional analysis that examine why it happened to data mining
that predicts what might happen in future [24]. The systems/technology used to
support decision-making can either be informal or formal. Spreadsheets represent
the simplest form of decision support and are often found in both SMEs [16] and
large organizations alike across the analytical spectrum [14; 20].
While the term Business Intelligence is relatively new, computer-based business
intelligence systems appeared, in one guise or other, close to forty years ago. BI as
a term replaced decision support, executive information systems, and management
information systems, [27]. With each new iteration, capabilities increased as
enterprises grew ever-more sophisticated in their computational and analytical
needs and as computer hardware and software matured.
BI systems are defined as follows:
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BI systems combine data gathering, data storage, and knowledge management with
analytical tools to present complex internal and competitive information to
planners and decision makers.
Implicit in this definition is the idea (perhaps the ideal) that business intelligence
systems provide actionable information delivered at the right time, at the right
location, and in the right form to assist decision makers. The objective is to
improve the timeliness and quality of inputs to the decision process, hence
facilitating managerial work.
Sometimes business intelligence refers to on-line decision making, that is, instant
response. Most of the time, it refers to shrinking the time frame so that the
intelligence is still useful to the decision maker when the decision time comes. In
all cases, use of business intelligence is viewed as being proactive. Essential
components of proactive BI are, [15]:Real-time data warehousing, • Data mining, •
Automated anomaly and exception detection, • Proactive alerting with automatic
recipient determination, • Seamless follow-through workflow, • Automatic learning
and refinement, • Geographic information systems • Data visualization
What Does BI Do?
BI assists in strategic and operational decision making. A Gartner survey ranked
the strategic use of BI in the following order, [29]:
1. Corporate performance management
2. Optimizing customer relations, monitoring business activity, and traditional
decision support
3. Packaged standalone BI applications for specific operations or strategies
4. Management reporting of business intelligence
One implication of this ranking is that merely reporting the performance of a firm
and its competitors, which is the strength of many existing software packages, is
not enough. A second implication is that too many firms still view business
intelligence (like DSS and EIS before it) as an inward looking function.
David Packard from Hewlett-Packard, who once said that marketing is too
important to be left to the organizational unit (sector/service/department) for
marketing and need to successful organizations. Consequently, these organizations
have accepted the thesis that creating, communicating and delivering value to
consumers, is not the responsibility of the personnel of the marketing
organizational unit only, but of all other employees as well (organizational units of
production, R&D, Accounting, Finance, HR Human Resource, IT Information
Technologies, etc..). [11].
Business intelligence is a natural outgrowth of a series of previous systems
designed to support decision making. The emergence of the data warehouse as a
repository, the advances in data cleansing that lead to a single truth, the greater
capabilities of hardware and software, and the boom of Internet technologies that
provided the prevalent user interface all combine to create a richer business
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intelligence environment than was available previously. BI pulls information from
many other systems.
Competitive Intelligence Analysis:
Next to knowing all about your own business, the best thing to know about is the
other fellow’s business.” John D. Rockefeller [2] Competitive intelligence (CI) is a
specialized branch of Business Intelligence. It is “no more sinister than keeping
your eye on the other guy albeit secretly” [12]. Competitive Intelligence is a
systematic and ethical program for gathering, analyzing and managing external
information that can affect your company’s plans, decisions and operations. In
other words, CI is the process of ensuring your competitiveness in the marketplace
through a greater understanding of your competitors and the overall competitive
environment. “You can use whatever you find in the public domain to ensure that
you will not be surprised by your competitors.” [12]. CI is not as difficult as it
sounds. Much of what is obtained comes from sources available to everyone,
including [12]:
• Government websites and reports • Online databases, interviews or surveys, •
Special interest groups (such as academics, trade associations, and consumer
groups), • Private sector sources (such as competitors, suppliers, distributors,
customer) or • Media (journals, wire services, newspapers, and financial reports).
The challenge with CI is not the lack of information, but the ability to differentiate
useful CI from chatter or even disinformation.
Of course, once a firm starts practicing competitive intelligence, the next stage is to
introduce countermeasures to protect itself from the CI of competitor firms. The
game of measure, countermeasure, and counter-countermeasure, and so on to
counter to the nth measure is played in industry just as it is in politics and in
international competition.
Literature Review
The core of business intelligence is the collective sense-making. In literature,
sense-making has been defined in different ways. It is an interpretative process
where people assign meaning to ongoing events [10]. It is the amplification of
weak signals and the search for contexts within small details fitted together for
sense-making [26]. It is considered as a creative and collective method that can
help the organization to give sense and see possibilities in the surrounding disorder
[3; 1]. [5] A positive aspect of subjective measurements is that the results show
how effective the users consider the intelligence products. However, subjective
measurements do not establish any monetary value for the effects of BI. [17]
Proposed a model referred to as VAS-IC (a French formulation of Anticipative
Strategic Environmental Scanning-Collective Intelligence) with a core process of
collective sense-making. The main steps of VAS-IC are described in figure 1
below [19], the organizations inter-viewed compare the cost of consultants to the
results obtained by the CI division and quantify the strategic deals that the CI team
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has been involved in and then compare the win / loss ratios to those deals where
they were not involved [16], the ?size-adjusted expenditure on items likely to
yield primarily long-term returns, is lower amongst small than large firms. SMEs
are slow to exploit opportunities offered by new technology to support their
growth. The ICT adoption behavior of SMEs is influenced by a range of factors
that can be ascribed to their unique characteristics [9] chief amongst these being
their limited resources, financial and otherwise This is reiterated by [22] stating
that the majority of the world‘s emerging economies indicate that micro, small and
medium enterprises will be the predominant enterprise for the foreseeable future as
these enterprises play a key role in economic growth and development. According
to [26] it is ?essential for small businesses in today‘s competitive environment to
take a strategic approach to their information needs if they wish to develop and
remain competitive.In a preliminary study, the basic idea is the following
Main Hypothesis 1: There is no impact of intelligence business on performance of
industrial firms
Hypothesis 1-1: There is no impact of Learning and growth Variable on
performance of industrial firms
Hypothesis 1-2: There is no impact of Financial Variable on performance of
industrial firms
Hypothesis 1-3: There is no impact of Customer Variable on performance of
industrial firms
Hypothesis 1-4: There is no impact of Knowledge economy variable on
performance of industrial firms
Methodology:
The sample of study is 50 industrial firms for the period 2006-2010 listed on
Amman Stock Exchange
The Model of Study:
The business intelligence for independent variable and this variable consist many
factors for how to measured .[5] has developed a measurement model called CI
Measurement Model (CIMM), which can be used to calculate the return on CI
investment (ROCII). Indeed, the resource-based theory of the firm reinforced the
idea that competitive advantage flows from unique resources of the organization
eventually leading to sustainable core competencies [25]. As capital and basic labor
became readily available to most organizations of any size, scholars began looking
for other factors that might explain why one firm is successful and another is not.
Parts of the discussion focused on intangibles, and we're all familiar with concepts
such as goodwill and brand equity, so the idea that intangible assets have value is
also nothing new. Indeed, the Tobin's Q measure of intangibles (market value to
replacement cost of assets) goes back decades. Newer measures developed during
the 1990's include the Balanced Scorecard [13].
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Independent Variables
Learning and growth Variable measured by: Administrative expenses per customer
(AE/C)Innovation: contribution to constant innovation is to be considered a task as
well as responsibility of the intellectual worker; it is part of his job. Learning and
teaching: intellectual work requires continuous self-learning as well as an
engagement to teach others and transfer knowledge [18].
Financial Variable measured by: return on investment (ROI)
Customer Variable measured by: Number of customer complaints (NCC)
From an economic point of view, unemployment is regarded as an expression of
several imbalances on the labor market that appears when the labor force offer
exceeds the demand, and on the market of goods and services the unemployment
appears when production exceeds demand. Therefore, the unemployment forms on
the basis of two processes: loosing the job by one part of the active population and
the increase of the job offer by reaching the legal age for work of new generations
[21].
Knowledge economy variable has engendered a great deal of interest in how
intangible knowledge assets or intellectual capital (IC) are managed in
organizations measured by: market value less book value (MV-LV).The concept
of the „knowledge worker” defines with reference to the context of post-industrial
transformation (new economy, information/ network/ knowledge/ learning
economy/ society. It is a conceptual reflection upon the complex and underlying
developments which evolved in the most advanced economies (with particular
respect to Japan and the USA). Peter F. Drucker is the first whose early assertions
with regards highly qualified intellectual labour have grown to meet the definition
criteria that is in use today to describe knowledge workers [18].
Dependent variable measured by: return on equity (ROE) as performance
indicator. The equation for Business performance was expressed in the following
equation
Performance (ROE) =a +?
1
AE/C+?
2
ROI +?
3
NCC+ ?
4
MV-BV+e
it
----Model (1)
Correlation Analysis:
A correlation coefficient measured the strength of a linear between the four
variables of A correlation Coefficient measured the strength of a linear between
two variables. The correlation results were shown in the Table (1).
Table 1. Pearson Correlation between variables BI and performance
Ind.
Variables
AE/C ROI NCC MV-BV
Person
Correlation
0.290* 0.327** 0.213 0.499***
Sig – 2
Tailed
0.065 0.042 0.112 0.001
Note: Asterisks (***) , (**) and (*) indicates significance at 1%,5% and 10%
respectively.
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This preliminary study suggests that a strong relationship may exist between
successful development of intellectual capital and organizational performance and
were significant at the 0.01 level .The correlations between AE/C, and Business
performance were positive and were significant at the 0.10 level, whereas
correlation between ROI and Business performance were positive and were
significant at the 0.05 level (2-tailed). Finally, no significant level between the
NCC and Business performance .Therefore, the study indicates that the correlations
between intellectual capital and Business performance were higher than others
variables.
Regression Analysis
In order to further reveal support for hypothesis 1, the factors that influenced
Business performance, the four variables of business intelligence process was used
in a multiple regression analysis. The regression procedure was employed because
it provided the most accurate interpretation of the independent variables.
Table 2. Regression Analysis Result
Ind.Variable
Const AE/C ROI NCC MV-BV
Dep. Var
ROE
3.886 2.994 3.121 2.417 5.194
0.031** 0.061* 0.041** 0.1119 0.0012***
St.co.beta ---- 0.310 0.390 0.190 0.480
VIF 1.081 1.441 1.418 1.484 1.145
Model -1- Model (1)
R
R
2
D-Watson
F-Statistic
Prob(F)
0.4462
0.214
5.954
14.158
0 .025
Note: Asterisks (***), (**) and (*) indicates significance at 1%, 5% and 10%
respectively.
The four independent variables were expressed in terms of the business intelligence
factor. The significant factors that remained in the regression equation were shown
in order of importance based on the beta coefficients.
In this study I used measures its BI performance in various ways. Measurement is
used as a tool to develop and improve BI activities as well as to demonstrate its
usefulness. Performance measures are chosen based on literature review The
methodology section illustrates the chosen focus areas pertaining to BI
measurement and they have a direct affect on the four chosen measurement focus
areas; financial, , learning and growth , customer and Knowledge economy
variables.
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BI performance is measured by determining the individuals and system activities
involved. These activities can be measured by using quantitative, qualitative and
time-related indicators. Quantitative measurement involves both input and output
indicators. Qualitative indicators include, e.g., the satisfaction of information users
and systematic information gathering is a prerequisite for efficient measuring.
There are two main challenges in measuring the effects of BI. First, the BI process
produces information and knowledge, which have to be utilized before the effects
are seen. The effects, if they occur, are intangible by nature, e.g. improved
decision-making ability. It is difficult to quantify these intangible phenomena.
These intangible effects may eventually have financial consequences. However,
distinguishing between the specific benefits received due to BI and the
achievements of ordinary decision-making is challenging .Thus, the second key
challenge in measuring the effects of BI is to distinguish what part of a
phenomenon, say increased market share, results from increased knowledge
produced by BI and what is caused by some other factors.
Table (2) showed the results of the regression analysis. To predict the of the
regression model, the multiple correlation coefficient (R), coefficient of
determination (R
2
), and F ratio were examined. First, the R of independent
variables (four variables) on the dependent variable (performance of firms, or
ROE) is 0.446, which showed that the performance had positive and high overall
association with the four attributes. Second, the R
2
is 0.214, suggesting that more
than 20% of the variation of performance was explained by the four attributes.
Last, the F ratio, which explained whether the results of the regression model could
have occurred by chance, had a value of 14.158 (p =0.025) and was considered
significant.
In other words, at least one of the four attributes was important in contributing to
performance. In the regression analysis, the beta coefficients could be used to
explain the relative importance of the four attributes (independent variables) in
contributing to the variance in s performance (dependent variable).
As far as the relative importance of the four business intelligence attributes is
concerned, MV/BV has, B1=0.480, p=0.0012) carried the heaviest weight for
performance, This measure will tend to favor larger firms, who may have more
intangible assets because of sheer size, not because they are clearly better at
managing such assets. Followed by ROI, B3=0.390, p=0.041 and AE/C, B2=-
0.310, p=0.061. Measuring the learning and growth sector is the most challenging
part in the balanced measurement process. Because of its intangibility, it is
challenging to measure e.g. organizational learning or if BI has resulted in better
decision-making but there is no significant to NCC variable. In conclusion, three
from four dimensions are significant. Thus, the results of multiple regression
analysis agree hypothesis 1, that there is relationship between the selected Business
intelligence and Business performance.
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Summary
This study has explored the role of BI in industrial firms on Jordan knowledge-
based from the perspectives of the key decision-maker. This paper has focused on
outlining the importance of tacit economic knowledge for the business intelligence
process measured by intellectual capital in industrial firms as one perspective affect
of performance and learning and growth process , customer and finally financial
perspective .These all variable exploring the business intelligence factor. The main
purpose of BI at firms is to enhance decision-making and service efficiency. The
main targets include efficiency, reasonable coverage of BI and user satisfaction. BI
comprises both internal and external business information, market information and
analysis. In fact, the whole concept of BI deals with providing insightful
information related to various business activities. Thus, it would be surprising if the
managers responsible for BI were not interested in obtaining intelligence
concerning its own operations.
The results indicates the Knowledge economy variable measured by intellectual
capital are more significant and effect of performance and this study has shown
that the provision of appropriate support with regard to BI is needed as BI plays a
crucial role to support decision-making in firms of all sizes more than learning and
growth or financial factor but there is no significant level for customer variable.
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POMIAR WP?YWU ANALIZY DANYCH BIZNESOWYCH NA WYDAJNO??:
BADANIA EMPIRYCZNE
Streszczenie: W niniejszym badaniu autor wyja?nia szybko zmieniaj?ce si? warunki
prowadzenia dzia?alno?ci gospodarczej, okre?la potrzeb? terminowej i efektywnej
informacji biznesowej która jest niezb?dne organizacjom, nie tylko do osi?gni?cia sukcesu
ale tak?e dla ich przetrwania . Business Intelligence (BI) to koncepcja, która odnosi si? do
filozofii kierowniczej oraz narz?dzie, które jest u?ywane, aby pomóc organizacji i
udoskonalenia informacji i podejmowaniu trafnych decyzji biznesowych.
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??????????????????????????????????BI?
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doc_273508531.pdf