Business Transformation: Deloitte Case Study of Daimler Trucks Asia

This report provides a comprehensive analysis of the Deloitte case study concerning Daimler Trucks Asia. It begins with an introduction to business model transformation and its importance. The discussion section examines the data-related issues faced by Daimler Trucks Asia, highlighting their impact on brand reputation and business. It then explores the benefits of Deloitte's project, such as cost savings, improved collaboration, and reduced timeframes. The report also addresses the risks associated with the data analytics project, including the potential loss of valuable data and confidential information. Furthermore, it discusses the future of Daimler Trucks Asia in the context of big data and disruptive innovations, emphasizing the need for continuous innovation to maintain a competitive edge. The conclusion summarizes the key findings, emphasizing the significance of business transformation for achieving stakeholder satisfaction and operational efficiency. References are provided to support the analysis.

Running head: DELOITTE CASE STUDY
Information System in Business: Deloitte Case Study
Name of the Student
Name of the University
Author’s Note:

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Table of Contents
1. Introduction............................................................................................................................2
2. Discussion..............................................................................................................................2
2.1 Explanation of Issue with Data at Daimler Trucks Asia with its Business Impact..........2
2.2 Discussion of Benefits of the Project of Daimler Trucks Asia........................................2
2.3 Discussion of Risks of the Data Analytics Project for Daimler Trucks Asia..................3
2.4 Future of Daimler Trucks Asia for Big Data and other Disruptive Innovations with
Justification for remaining Competitive.................................................................................3
3. Conclusion..............................................................................................................................3
References..................................................................................................................................4

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1. Introduction
Business model transformation is extremely helpful in capturing new growth
opportunities, reduction of expenses, improvement in efficiencies and finally staying much
ahead of the consumer preferences (Ogiela and Ogiela 2014). This report will be providing a
brief analysis of the case study of Daimler Trucks Asia.
2. Discussion
2.1 Explanation of Issue with Data at Daimler Trucks Asia with its Business Impact
Daimler Trucks Asia is the integral subsidiary in the largest truck manufacturing
organization, known as Daimler AG for the purpose of leading the industry of commercial
vehicle into the future (Daimler Trucks Asia. 2019). The complete business model of this
particular company was to be transformed into one, which could leverage insight power. A
disruption has started in quality management department regarding safety or performance
standards (Ullah and Lai 2013). This type of quality issue is highly impacting their brand
reputation and business.
2.2 Discussion of Benefits of the Project of Daimler Trucks Asia
There are numerous important advantages of this project of Daimler Trucks Asia
(Frank et al. 2014). The popular organization of Deloitte has helped out Daimler Trucks Asia
to save their millions of dollars regarding recalling of repairs by proper deployment of a
cognitive solutions, which could improvise the overall capability of a client in prediction,
detection as well as remediation of the repairs. Collaboration is also enhanced to a higher
level with this project with Deloitte (Laudon and Traver 2016). Time period is also reduced
and there would be high level of social media engagement.

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2.3 Discussion of Risks of the Data Analytics Project for Daimler Trucks Asia
The various risks related to the data analytics project in Daimler could be referred to
as extremely vulnerable for the organizational data (Veit et al. 2014). While dealing with the
structured and unstructured data like call centre record, live data from connected trucks and
technician comments; it might occur that the data gets lost and there would not be any chance
of data recovery under any circumstance (Rajnoha et al. 2014). Moreover, it could also lead
to major loss in organizational profits after losing the confidential data completely (Wu,
Straub and Liang 2015).
2.4 Future of Daimler Trucks Asia for Big Data and other Disruptive Innovations with
Justification for remaining Competitive
The future of Daimler Trucks Asia for the big data as well as any other disruptive
technology is eventually termed as quite effective (Baharuddin et al. 2015). By subsequent
continuation of innovation as well as its major dedication to insight power, this particular
organization would be determined in the position to help out for leading the entire industry of
truck manufacturing for creation of newer services as well as claiming the spot as the
futuristic globalized company (Cassar, Ittner and Cavalluzzo 2015). They would remain
competitive and gain competitive advantages by simply enhancing their opportunities through
innovativeness.
3. Conclusion
Hence, conclusion could be drawn that business transformation is being referred to as
a procedure to fundamentally altering the technologies, people and procedures across the
entire business for achievement of every measurable improvement for stakeholder
satisfaction, effectiveness and efficiency. The above report has clearly demonstrated the case
study of Daimler Trucks Asia.

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References
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halal concept and the importance of information on halal food business needed by potential
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Sciences, 5(2), pp.170-180.
Cassar, G., Ittner, C.D. and Cavalluzzo, K.S., 2015. Alternative information sources and
information asymmetry reduction: Evidence from small business debt. Journal of Accounting
and Economics, 59(2-3), pp.242-263.
Daimler Trucks Asia. 2019. [online]. Accessed from
https://www2.deloitte.com/us/en/pages/about-deloitte/articles/daimler-truck-manufacturing-
case-study.html [Accessed on 18 August 2019].
Frank, U., Strecker, S., Fettke, P., Vom Brocke, J., Becker, J. and Sinz, E., 2014. The
research field “modeling business information systems”. Business & Information Systems
Engineering, 6(1), pp.39-43.
Laudon, K.C. and Traver, C.G., 2016. E-commerce: business, technology, society.
Ogiela, L. and Ogiela, M.R., 2014. Cognitive systems for intelligent business information
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Rajnoha, R., Kádárová, J., Sujová, A. and Kádár, G., 2014. Business information systems:
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Ullah, A. and Lai, R., 2013. A systematic review of business and information technology
alignment. ACM Transactions on Management Information Systems (TMIS), 4(1), p.4.

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Veit, D., Clemons, E., Benlian, A., Buxmann, P., Hess, T., Kundisch, D., Leimeister, J.M.,
Loos, P. and Spann, M., 2014. Business models. Business & Information Systems
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Wu, S.P.J., Straub, D.W. and Liang, T.P., 2015. How information technology governance
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