Business Intelligence Tools: Implementation, Value, and Challenges

This report provides a comprehensive analysis of business intelligence (BI) tools within multinational organizations. It begins by identifying key factors that influence the successful implementation of BI, such as organizational culture, data management as a valuable asset, and the selection of appropriate technology, including the importance of data analysis. The report then evaluates how BI tools enhance value and support decision-making processes (DM) through data-driven insights, improved customer experience, and data accuracy. Furthermore, it discusses the advantages and disadvantages of using BI, including real-time data access and mobile platform integration, as well as potential issues like varied interpretations of data. Finally, it offers recommendations for managers and decision-makers on leveraging BI effectively, concluding that the strategic application of BI can significantly improve business outcomes. This report aims to provide a clear understanding of BI's role in modern business operations and its impact on organizational performance.

Business Intelligence

INTRODUCTION................................................................................................................................1
MAIN BODY......................................................................................................................................1
1. Identify the factors that affect the successful implementation of Business Intelligence Tools
in Multinational organisations.....................................................................................................1
2. Evaluate that how BI tools can add value and support DM processes in organisations.........3
3. Advantages and Disadvantages of using BI in organisations...................................................5
4. Recommendations suggested for managers or decision makers regarding using and
applying BI in their organisations................................................................................................8
CONCLUSION....................................................................................................................................9
REFERENCES...................................................................................................................................10

INTRODUCTION
Business Intelligence (BI) puts together information intelligence, data analysis, data engineering,
technology resources and applications and methods to help companies make more evidence-driven
decisions (Božič and Dimovski, 2019). In reality, they realize that have advanced business intelligence
because they have a holistic understanding of the data from the enterprise and use the data to
accelerate improvement, remove inefficiencies, and respond easily to changes in the demand or supply.
Earliest business intelligence (BI) is known as the Cyclopædia of Economic and Industry Anecdotes by
Richard Millar Devens. They used the word to explain how, before their rivals, the banker Sir Henry
Furnese had earned income by obtaining and acting on knowledge regarding the environment require
Enterprises should use market intelligence to help a wide variety of company decisions ranging from
tactical to strategic. Basic business considerations placement or selling of the goods.( Zaby and Wilde,
2018) This assessment cover several topics such as some factors which affect the successful
implementation of BI in the organization and how it generate values to aid DM process. In addition, it
includes the advantages and disadvantages of using business intelligence in the entity. Along with it,
provide some recommendation for decision makers that how to use BI process in their organizations.
MAIN BODY
1. Identify the factors that affect the successful implementation of Business Intelligence Tools in
Multinational organisations
There are several factors which affect the organization while management implement BI Tools for
the successful outcomes (Factors that affecting the successful implementation of BI, 2019). In order to
get success in their operations, multinational organizations implemented BI tools but make sure to
consider such factors before making any business decisions and these factors discussed below:
Figure 1 Business Intelligence, 2020.
1

 Culture is King: Not all company is able to adopt a tech framework like a BI tool, or available.
The right approach for daily analysis of data and insights for operational decision-making is
lacking in many organizations (Saura and Bennett, 2019). Although businesses have long
gathered information regarding their customers, products and markets, processing and
exploiting this data is not inherently inherent, consistent, or wide-ranging management
practices.( Zaby and Wilde, 2018) Companies are still discouraged from accepting data from the
top, with executives at C-level having over-reliance and excessive trust in their expertise and
good instincts. This needs to start with the basics down to create a data-driven community. The
data should be available to all, and everyone needs to realize the importance of such BI Tools for
their individual positions and the overall market success, only then can the BI approach become
part of the culture.( Zaby and Wilde, 2018)
 Value data as assets: The growing reliance in our everyday lives on emerging technologies has
turned every business into a digital business. Data is gathered in the organization, frequently in
distant locations, agencies that are isolated and fragmented silos. This outcome in a
disassociated planning of the business and badly informed decision making.( Mariani, and et.al.,
2018) Data should be regarded and handled as a valuable business asset, with the necessary
degree of care and consideration paid to such an asset. When an organization is powered by
data and decides to adopt Business Intelligence, the next steps are to set up the tools and
processes to ensuring the raw data is as reliable and timely as it can be transformed into
actionable information.( Mariani, and et.al., 2018)
 Implement the right technology: The most important factor to be considered when choosing
the correct BI tool is the 'backend' where information is in structured way. Factors such as
options for data connection and ETL functionality will eventually depend on the ability of the
computer vision to retrieve clean and incorporate the data needed as necessary to provide such
visualizations (Scholtz, Calitz and Haupt, 2018). If they really don't tell the full story or identify
the right or useful information, there's really no value in having the best looking maps. While
cultural heritage, quality information and actively involved stakeholders play a critical role in a
successful BI action plan, in the end it is the decision of the technology involved that will make
things happen, and those people choose to enforce it.( Sun, and et.al., 2018) For example VISA
analytical platform that is powerful application that provides data-driven insights and
performance objectives all supported by Visa’s worldwide payment system and cutting-edge
computer engineering.
2

 Analysis is Key: When introduced the BI method is in place and quality data flows into the
centralized server from departments and services, the next crucial process for BI
implementation is its application in the performance improvement phase, and the effectiveness
of this is measured by the results of the very first three phases (Liang and Liu, 2018). Taking
data-based business choices is a competitive edge and this is a strategic advantage, since it is
not currently commonly recognized. Data analysis becomes far more efficient and effective with
right culture, adequate and reliable data. With better analytics people can start making smart
choices based on the best available intellectual ability. The business results of taking decisions
can be traced back to show how data analysis and BI affected these judgements, created an
opportunity for revenue generation, increased operating efficiency gains, and provide better
customer service.( Sun, and et.al., 2018) For example: By using SAS BI tool, organization able to
monitor the information and also design cloud base enterprises analysis for large entities that
covered several features such as marketing report, data source, customize dartboard, as-hoc
analysis etc.
From the overall analysis it has been concluded that organization need to evaluate above discussed
factors and build operational strategies accordingly where they use BI tools for the successful outcomes
but also ensure that such factors in decision making process.
There are four factors that can affect BI implementation performance, and eventually have a positive
effect on final outcome by using such VISA and SAS software (Tripathi, Bagga and Aggarwal, 2020).
Those that they haven't mentioned above and that come later in time are, determining which decision in
the end based on the results, tracking the success of decisions taken and continuously updating and
improving the BI method, presenting data and visualizations and results. When BI is more integrated in
the business culture, this will have a dramatic effect about how they approach the clients, produce and
sell new goods and services and build tactics that can help the end result.
2. Evaluate that how BI tools can add value and support DM processes in organisations
BI tools are the access and interpret data sets which provide users with comprehensive details on
the state of the market in reports, overviews, dashboards, diagrams, charts and maps. There are several
ways of BI tool which helps the organization or support DM process through which create values or
helps in generating revenue or making business more productive (Value of BI tools, 2020). Some of them
are as follow:
3

Figure 2 Business Intelligence tool, 2020.
Decision making: BI tool generate key value through transforming client data into well-structured
form, analyzable insights or actual market information that guides strategic decision-making. Also at
core of good decision-making is a simple, unified storehouse that pulls evidence from all the company's
operations and customer experiences together.( Liang, and Liu, 2018) Excellent BI seems to have access
to all corporate information in a centralized unified location with a dashboard that contains data from
various departments such as marketing, financial management and inventory management to give a
holistic picture of the business, its clients and their business entities.( Liang, and Liu, 2018) This means
business decisions are supported by facts and not on assumptions.
Customer experience: Another main value of BI tools would be that they offer valuable
knowledge that lets businesses understand how clients communicate with the organization. Accessing
all customer data in one folder, from everywhere at a certain time, significantly improves data
consistency and maintenance of customer relationships (Zaby and Wilde, 2018). An IB tool enabling the
company is to dramatically increase the customer loyalty service and experience. Analytics tools
enhance the market segmentation of their various client groups, attempting to identify in which
resources must be efficient performance and whether the business attracts the right clients to fulfil and
ensure economic production goals.( Zaby and Wilde, 2018)
Data accuracy and compliances: Having data in separate departments makes it practically difficult
to get a 360 degree comprehensive view of the company, certain clients, processes and activities
(Minato, Wapenaar and Ghose, 2020). BI data's centralized nature significantly increases accountability
and expose mistakes leading to failures and unused money. This is essential that the information is up-to
- date and consistent with global data security laws regulating how companies collect, process, and use
4

personal data. Enterprises can tackle data privacy and improve data governance through the
introduction of BI tools.
Strong corporate intelligence would be a primary strategic objective of each organization. The
useful data supplied by BI tools allows business managers to optimize planning and respond quickly and
effectively throughout all processes of decision-making. By making effective business decisions provide
customer services, maintain accuracy in data handling etc. are helps in generating value for the
organizations (Bordeleau, Mosconi and Santa-Eulalia, 2018). In addition, it will further helps in Data
Mining process in the business where data collected in single platform and every member of the
organization can use it for the better performance. With the of SAS BI tool, organizations able to analyse
the matrix report of users which help the managers or top management to make effective decisions and
achieve their business goals & objectives through supporting DM process. By using above discussed
points help the BI tools to add value in the organizations.
3. Advantages and Disadvantages of using BI in organisations
There are several advantages as well as disadvantages which organization face while they
implementing business intelligence tool for better performance or productivity (Advantages or
disadvantages of Business Intelligence, 2020). Some of them are as follow:
Advantages:
 Global BI switches to mobile platforms (Richards and et.al., 2019). They also have BI in the
Cloud, so if business takes rest for long time and they need to close a sale that means
organization will still have the details when they need it.
5

 BI systems are more engaging than ever, due to the numerous technological enhancements over
the years (Lennerholt, van Laere and Söderström, 2018). It makes for more accurate and
consistent display of the results.
 Supervisor ought to take a judgment split-second. This means company has the up-to -
date knowledge available (Caseiro and Coelho, 2018). Today's BI apps will deliver knowledge to
organisations in real time, so that those involved will change policies or approaches
data automatically.
 If business use BI tools and apps, several techniques are able nowadays that will help them to
work on a scale that's perfect for the company (Božič and Dimovski, 2019). It covers pay-per-use
plans, plans to download as well as other pay-as-you-go services. Businesses will have the
information they require if they need it, but during those periods when they do not need it, they
wouldn't have to spend for it.
 Business Intelligence enables organizations to properly monitor how their Key Performance
Indicators (KPIs) have been achieved (Bordeleau and et.al., 2018). The method framework will
look at the large data, help create valuable metrics, and this essentially makes a organization
more successful at what it is doing.
Disadvantages:
 Various people are likely to be looking at the information umbrella and expect two completely
different results, which imply a company needs to invest its time trying to find common ground
(Torres Sidorova and Jones, 2018).
 Business intelligence can allow workers to access the information using personal devices
(Mariani and et.al., 2018). The data gathered on a specific group may well be viewed by some as
personal data that they could not want an individual to be accessed.
 If people are using mobile BI apps therefore the hacking threat will endanger the confidential or
proprietary details (Puklavec, Oliveira and Popovič, 2018). At Target, Home Depot, and other
retailers, data hacks prove that other systems are not 100 per cent safe either. Except if their
system is totally separated with an online platform, the danger have a security flaw is something
that should always be constructively considered.
 Even businesses that use Smartphone or Cloud-based alternatives for their BI applications can
find it difficult with the expenditures associated with data planning (Masa’Deh and et.al., 2018).
Business intelligence as just a business sector has many vendors and everyone’s cloud services
can be quite unique from each other. Not that every vendor has price transparency either. Insert
6

to the information overages or premium content and it could be too much for even an
inexpensive pay-as-you-go system.
 If technology evolves, the rules do change, and if a organization does not develop its BI
programs, they may face a disastrous failure in the event of a security incident (Shabbir and
Anwer, 2018).
 Some are only beginning to understand what BI technologies can bring. Others have successfully
managed their Big Data for years (Scholtz, Calitz and Haupt, 2018). Not every company will face
this drawback and for some time coming those who do may consider restricted availability.
 Many options for the BI are currently available. Most can have one particular surface (Fallah and
et.al., 2018). They may have to spend in a whole umbrella of infrastructure to make sure that BI
is completely optimized and get the best out of the data analytics.
Above discussed advantages or disadvantages help the organization or management to
understand how business intelligence work and how in future it provide success or can lead the failure
as well (Puklavec, Oliveira and Popovič, 2018). Some of the real organizational case example where by
using BI helps the business to get success or failure as well. In fact, the advantages and disadvantages of
market analytics indicate that the advantages greatly outweigh the risks of applying big data
approaches. Look for tech solutions and digital resources to get the best out of the knowledge they have
already so organizations can make the correct strategic choices that keep their year after year
profitable.
Example of BI success:
In Chipotle, company face the issues regarding differing data sets which prevented teams from
having restaurant perspectives unity (Successful implementation of BI tool, 2020). Chipotle migrated to a
new, self-service BI network with their traditional BI approach. This helped them to establish a
consolidated view of the process so they could monitor the success of restaurant business on a regional
scale. Now that workers have much more data exposure, monitor production rates for critical programs
have doubled from monthly to quarterly and saved hundreds of hours.
Example of BI failure:
This case shows important one minute information missing from scenario in the entire data
mining cycle which eventually led to a catastrophe scenario for a major Canadian bank. The incident
involved an outside supplier developing a logistic solution model for the attracting new client for a given
financial commodity of a very well-known Canadian bank (Business failures, 2018). Selected model was
constructed and was running really well when based on the results of the affirmation. The Score was not
7

generated automatically by the BI tool during the scoping phase. The consumer had to consider the
effects manually of the model creation process from the output equation, and create a scoring protocol
to rank a given list of bank clients.
4. Recommendations suggested for managers or decision makers regarding using and applying BI in their
organisations
There are several ways which help the organizations to improve business intelligence (BI) for the
maximisation of production as well as operational performance (Richards And et.al., 2019). It will help
the decision makers or managers to build strategies for the growth organization and it discussed below:
 Identify the return of their marketing strategy: "Market intelligence is critical in a world filled
with applications, social media channels, advanced analytics and pay per click promotions to
support small companies find out whether the marketing plan those who've invested in is
delivering ROI (return on investment).( Richards, and et.al., 2019)
 Drive knowledge from a sea of data: The business intelligence is more critical than before
today. In the last two years only, 90 per cent of the data that occurs in the modern world has
been generated (Sun, Sun and Strang, 2018). The pace of data production will only be
accelerating in the future. The biggest explanation for this is the expansion of social media
platforms and the rising number of customers at crazy speeds publicizing info.
 Identify that which activity drives revenue for the business: While BI used in wide word, it
will know precisely what it generate sales for the company. Business intelligence knows how and
where (media outlets and through posts, photos, advertising, podcasting, etc.) target consumer,
receives their content, what will cause them to buy and subscribe, and executes a plan to take
advantages of that.( Richards, and et.al., 2019)
 Personalized their sales strategy and anticipated objectives: "Business intelligence allow
learning about other companies they are attempting to deal with in some way. In addition,
8

selling managers are investigating this knowledge in order to be prepared for customer-specific
concerns. It is especially helpful to know whether the product they are seeking to market is
reducing costs, has raised employee turnover, and reduced revenue statistics.( Richards, and
et.al., 2019)
CONCLUSION
From the overall discussion it has been observed that business intelligence tool used by almost
every organization to manage their data and further formulate strategies regarding improving their
revenue or maximise productions. By using such BI Tools, organizations can face the success in their
operations and sometime they also has to face the failure because in ineffective implementation. BI
tools also used to add value in their performance and which support DM process. In addition, there are
several advantages as well as disadvantages of BI tools that are essential to understand and build future
strategies accordingly. Along with it, there are some recommendations for managers to improve their
decision making process.
9

REFERENCES
Books & Journals
Bordeleau, F. E., Mosconi, E., & Santa-Eulalia, L. A. (2018, January). Business Intelligence in Industry 4.0:
State of the art and research opportunities. In Proceedings of the 51st Hawaii International
Conference on System Sciences.
Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data in
hospitality and tourism: a systematic literature review. International Journal of Contemporary
Hospitality Management.
Puklavec, B., Oliveira, T., & Popovič, A. (2018). Understanding the determinants of business intelligence
system adoption stages. Industrial Management & Data Systems.
Richards, G., Yeoh, W., Chong, A. Y. L., & Popovič, A. (2019). Business intelligence effectiveness and
corporate performance management: an empirical analysis. Journal of Computer Information
Systems, 59(2), 188-196.
Sun, Z., Sun, L., & Strang, K. (2018). Big data analytics services for enhancing business
intelligence. Journal of Computer Information Systems, 58(2), 162-169.
Minato, S., Wapenaar, K., & Ghose, R. (2020). Elastic least-squares migration for quantitative reflection
imaging of fracture compliances. Geophysics, 85(6), 1-66.
Zaby, C., & Wilde, K. D. (2018). Intelligent business processes in CRM. Business & Information Systems
Engineering, 60(4), 289-304.
Liang, T. P., & Liu, Y. H. (2018). Research landscape of business intelligence and big data analytics: A
bibliometrics study. Expert Systems with Applications, 111, 2-10.
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of
absorptive capacity. International journal of information management, 46, 93-103.
Saura, J. R., & Bennett, D. R. (2019). A Three-Stage method for Data Text Mining: Using UGC in Business
Intelligence Analysis. Symmetry, 11(4), 519.
Scholtz, B., Calitz, A., & Haupt, R. (2018). A business intelligence framework for sustainability
information management in higher education. International Journal of Sustainability in Higher
Education.
Tripathi, A., Bagga, T., & Aggarwal, R. K. (2020). Strategic Impact of Business Intelligence: A Review of
Literature. Prabandhan: Indian Journal of Management, 13(3), 35-48.
Richards, G. & et.al., (2019). Business intelligence effectiveness and corporate performance
management: an empirical analysis. Journal of Computer Information Systems, 59(2), 188-196.
Caseiro, N., & Coelho, A. (2018). Business intelligence and competitiveness: the mediating role of
entrepreneurial orientation. Competitiveness Review: An International Business Journal.
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of
absorptive capacity. International journal of information management, 46, 93-103.
Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence
and analytics: A dynamic capabilities perspective. Information & Management, 55(7), 822-839.
Puklavec, B., Oliveira, T., & Popovič, A. (2018). Understanding the determinants of business intelligence
system adoption stages. Industrial Management & Data Systems.
Masa’Deh, R. E., & et.al., (2018). The impact of business intelligence systems on an organization’s
effectiveness: the role of metadata quality from a developing country’s view. International
Journal of Hospitality & Tourism Administration, 1-21.
Shabbir, J., & Anwer, T. (2018). Artificial intelligence and its role in near future. arXiv preprint
arXiv:1804.01396.
10