Business Intelligence Knowledge Management

This presentation explores the concept of Business Intelligence Knowledge Management and its impact on Siemens. It discusses the strategic information needs of the business, the viability of delivering a BI solution, risk and benefits assessment, data management issues, the use of data mining, the role of data visualization, adoption and implementation strategy, change management, and BI management.

Business Intelligence Knowledge Management
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Business Intelligence Knowledge Management
The business’ strategic information needs that are not currently being addressed adequately
 From the ‘Internet of Trains’ case study, it’s evident that the performance of Siemens company
has been greatly boosted by the use of sensor data. The sensor data helps the Siemens Company
to keep the train operators on track, and this has helped to reduce the cases of train failures.
 Although the cases of train failures have been greatly reduced, there are still some needs which
are yet to be addressed adequately. Siemens has concentrated so much on addressing the train
failures which result from the engine problems and has neglected the other problems and failures
which result from other components and systems of the trains. Human factor or human error is
also yet to be addressed adequately and that’s why there are still many failures experienced in the
train industry due to human error.

The viability of delivering a BI solution
 Delivering a BI solution will be very viable and very crucial in improving the overall performance
of Siemens which will consequently help to reduce the cases of train failures reported in the train
industry.
 A BI solution will help the company to consider and apply the best technologies, applications, and
other digital practices which will the company in the processes of information collection, analysis,
integration, and presentation of the information in the required formats (Tian, Chin, and Karg,
2016, pp.4-6). This will eventually help in improving the decision-making processes undertaken
by the company, and this will help the company to come up with the best decisions and strategies
which can help in reducing the cases of engine failures reported in the train industry (Thamir and
Poulis, 2015, pp.34-37).

Risk assessment associated with delivering a BI solution
 There are many risks associated with delivering a BI solution in Siemens, and so, it’s very
important for the company to do a good risk assessment before delivering the BI solution. One of
the main risks which face the process of delivering a BI solution is the high cost which will be
incurred in the process of delivering the BI solution, and this high cost may not be recovered
easily.
 As already said, the process of delivering a BI solution requires the company to embrace and
introduce new technologies, applications, and other digital practices which will help in
implementing the BI technology in the firm. These technologies, applications, and the other
digital practices will cost the company huge amount of money, and the company may not recover
this money after implementing the BI technology in the firm if it doesn’t plan the process well
(Richards, Yeoh, Chong, and Popovič, 2019).

Benefits assessment associated with delivering a BI solution
 Delivering a BI solution is expected to yield many benefits to Siemens and to the train industry. The
major benefit which will be realized through delivering of the BI solution will be a significant drop
in the number of train failures and problems experienced in the train industry. It’s also good to note
that there will be other secondary benefits which will be realized through delivering a good BI
solution in the company where some of the main secondary benefits which will be improved quality
of services offered by the company and improved efficiency in the operations undertaken by the
company (Olszak, 2016, pp.105-123). This will help the company and the train industry to have
more customers who will help them to enjoy many benefits.
 A comprehensive assessment and analysis of the benefits associated with delivering a BI solution
can be done using a cost-benefit analysis which helps organizations to compare all the expected
costs of implementing a new project to the expected profits or benefits which will be realized from
the project.

Data management issue
 There are many data management issues which affect Siemens and the train industry. These data
management issues must be given the appropriate consideration especially during this critical
time when Siemens wants to come up with a new BI solution which will help to improve its
performance and reduce the cases of train failures and other problems reported in the train
industry.
 In the process of delivering the new BI solution, Siemens will have to do extensive research to
gather all the relevant data and information which will help it to deliver and implement the new
project successfully. For the company to handle the expected new huge volumes of data and
information effectively, it will have to design other new and modern databases which are capable
of handling and managing huge and complex volumes of data effectively.

How data mining can be used by Siemens to improve its performance
 Data mining can be described as the process applied by organizations to help them in arranging
and sorting out their large and complex data (Witten, Frank, Hall, and Pal, 2016). Data mining
helps the organizations to examine, analyze, and sort out the huge and bulky data in their
databases, and this examination, analysis, and sorting consequently help the organization to
make good and effective use of the data (Larose, 2015).
 It’s good to note that the data and information gathered and stored in the databases of
organizations are of different and varying uses, and that’s why organizations undertake the
process of data mining to help them in sorting and categorizing their data and information. This
sorting and categorization help the organizations to make the best use of all the data and
information in their databases (Montgomery and Purnell, 2018).

The role which would be played by data visualization
 Data visualization is a broad term which encompasses different techniques which are used to
improve the presentation and the readability of data (Ward, Grinstein, and Keim, 2015). Data
visualization helps data analysts in converting data and information from one form to another,
and this conversion helps in the presentation of data in the best and the most suitable forms
required in different areas.
 Data visualization would play a very important role in Siemens as it would help the designers and
the data analysts to present the data they collect and store in different forms of their choice. The
data can then be used to prepare visual graphs or some other appropriate images which may be
required by the organization. Graphical representation of data is very important in organizations
as it helps the organizations the organizations to come up with the appropriate graphs and other
visual images which can help to show the trends of the performance of the organizations.

Adoption and implementation strategy
 The process of delivering BI solution can be very effective and successful if done appropriately.
If we assume that Siemens currently uses Oracle as its database and uses SAP to manage its
corporate systems, and all the staff members have reasonable access to various computing
resources; the introduction of the BI solution will not overload the servers of the company, and
thus will work appropriately to improve the performance of the company.
 There are different BI options which exist in the market today. Some of the most important BI
options which can work well with Siemens to reduce the cases of train failures and problems
include reporting and querying software which consist of applications which can be used in the
extraction and presentation of data, online analytical processing (OLAP) software which can be
used in the processing of the data and information used by the organization, among other
options.

Change management
 The way data is owned, used, and shared in Siemens can be changed effectively to enhance data
security and data management process in the organization. The role of data management and
protection is mainly assigned to the database administrator and the one who can facilitate the
process of changing the data ownership, usage, and sharing in the organization. This process of
changing should only be done when necessary, and should not violate the security and the
privacy of the organization’s data.
 Changing the organizational culture in relation to IT services should also be done when
necessary. This change should be implemented by the IT experts of the organization who are
always assigned the role of managing and controlling all the IT services of the organization. The
change, should, however, not violate the security and the privacy of the data.

BI management
 BI management should be left to the qualified IT experts of the organization. These experts
have a good understanding of the BI framework which is a framework which helps in the
identification and maintenance of the BI strategy. These IT experts are responsible for
managing the business intelligence techniques applied in the organization to make sure these
techniques are helpful to the organization and work to realize the desired targets. To achieve the
best results from BI management, Siemens should make sure it gives out the role of BI
management to the most qualified IT experts who will work to achieve all the set targets.

References
Boardman, A.E., Greenberg, D.H., Vining, A.R. and Weimer, D.L., 2017. Cost-benefit analysis:
concepts and practice. Cambridge: Cambridge University Press.
Coronel, C. and Morris, S., 2016. Database systems: design, implementation, & management.
Boston: Cengage Learning.
Haimes, Y.Y., 2015. Risk modelling, assessment, and management. New Jersey: John Wiley & Sons.
Larose, D.T., 2015. Data mining and predictive analytics. New Jersey: John Wiley & Sons.
Montgomery, C.S. and Purnell, S.K., 2018. Customizable data aggregating, data sorting, and data
transformation system. U.S. Patent 9,985,609.
Olszak, C.M., 2016. Toward better understanding and use of Business Intelligence in
organizations. Information Systems Management, 33(2), pp.105-123.

Patassini, D., 2017. Beyond benefit cost analysis: accounting for non-market values in planning
evaluation. London: Routledge.
Richards, G., Yeoh, W., Chong, A.Y.L. and Popovič, A., 2019. Business intelligence effectiveness and
corporate performance management: an empirical analysis. Journal of Computer Information
Systems, 59(2), pp.188-196.
Saket, B., Srinivasan, A., Ragan, E.D. and Endert, A., 2018. Evaluating interactive graphical
encodings for data visualization. IEEE transactions on visualization and computer graphics, 24(3),
pp.1316-1330.
Thamir, A. and Poulis, E., 2015. Business intelligence capabilities and implementation
strategies. International Journal of Global Business, 8(1), pp.34-37.

Tian, J., Chin, A. and Karg, M., 2016. Digital services in the automotive industry. IT
Professional, 18(5), pp.4-6.
Walker, G.H. and Stanton, N.A., 2017. Human factors in automotive engineering and
technology. Florida: CRC Press.
Ward, M.O., Grinstein, G. and Keim, D., 2015. Interactive data visualization: foundations,
techniques, and applications. AK Peters/CRC Press.
Witten, I.H., Frank, E., Hall, M.A. and Pal, C.J., 2016. Data Mining: Practical machine
learning tools and techniques. Massachusetts: Morgan Kaufmann.

The BI tools
 There are many tools which can be used to implement business intelligence strategy at
Siemens. The two most common tools which can be used are PowerPivot and the
tableau. These two BI tools have many features in common, and thus any of the two
tools can be applied accordingly to implement the new BI strategy.
 These tools help to represent the data visually in graphs or charts which makes it possible
to show the trends of some of the important issues affecting the train industry. Some of
the graphs/charts (derived from the excel work) which can prepared from these BI tools
are shown below: