Analyzing IS/IT Innovation: Amazon, Netflix, Apple, Mitsubishi Cases

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This report examines the use of Information Systems and Information Technology (IS/IT) for innovation through four case studies: Machine Learning in Amazon, Cloud Computing in Netflix, Artificial Intelligence in Apple, and Robotics in Mitsubishi. Each case study provides a background, discusses success factors, and analyzes the impact of internal and external factors on the implementation of IT-enabled innovation. Amazon's use of machine learning for data analysis and sales forecasting, Netflix's adoption of cloud computing for streaming services, Apple's integration of artificial intelligence for product development and customer support, and Mitsubishi's application of robotics are explored. The report concludes with recommendations based on the case studies, emphasizing the importance of leveraging technological developments to meet organizational needs and customer requirements effectively.
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Running head: USE OF IS/IT FOR INNOVATION
USE OF IS/IT FOR INNOVATION
Name of student:
Name of university:
Author’s note:
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1USE OF IS/IT FOR INNOVATION
Table of Contents
Introduction....................................................................................................................3
Discussion......................................................................................................................3
Case study 1: Machine Learning in Amazon.............................................................3
Background study of machine learning in Amazon...............................................3
Success factors of machine learning in Amazon....................................................4
Impact of external factors and internal factors.......................................................4
Case study 2: Cloud computing in Netflix.................................................................5
Background of Netflix............................................................................................5
Success factors of cloud computing in Netflix......................................................6
Impact of external and internal factors on cloud computing in Netflix.................6
Case study 3: Artificial intelligence in Apple............................................................7
Background of artificial intelligence in Apple Inc.................................................7
Success factors of artificial intelligence in apple...................................................7
Impact of external and internal factors...................................................................8
Case study 4: Robotics in Mitsubishi........................................................................9
Background study...................................................................................................9
Success factors of robotics in Mitsubishi...............................................................9
Impact of external and internal factors.................................................................10
Recommendation..........................................................................................................10
Conclusion....................................................................................................................11
References....................................................................................................................12
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2USE OF IS/IT FOR INNOVATION
Introduction
This report aims to discuss the topic Use of IS/IT for innovation. Four case studies are
selected for this report. The selected case studies are the ML in Amazon, AI in Apple,
Robotics in Mitsubishi, and Cloud computing in Netflix. A detailed discussion of background
is provided of all the case studies. The success factors of implementation of IT enabled
innovation in the cases studies is provided in this report. A brief discussion of the impact of
external and internal factors on the implementation of IT enabled innovation is provided in
this report. Some recommendation on the basis of the case studies is discussed in this report.
Lastly, this report concludes with an appropriate conclusion.
The utilisation and the activation of the IT enabled innovation is comprehensively
used in the companies for meeting the organisational needs and fulfil the requirements of the
customers. The technological developments in the modern era is helping the organisations in
performing business functions more efficiently and effectively.
Discussion
Case study 1: Machine Learning in Amazon
Background study of machine learning in Amazon
The machine learning in Amazon offers the wizards and tools of visualisation that
guides through the method of creating models of machine learning without performing the
task of learning complex technology and algorithms of machine learning (Papernot,
McDaniel and Goodfellow 2016). The built-in data processors of the service, the scalable
algorithms of machine learning, tools of model visualisation and the interactive data, and the
alerts of quality helps in building and refining the models easily. The prediction API of
Amazon Machine learning can be utilised for generating huge amount of predictions for any
application (Meng et al. 2016). Huge amount of predictions can be requested for big numbers
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of the records of data at the same time by utilising the API of batch prediction, or utilise the
API real-time for obtaining predictions for the unique data records and utilise them within the
interactive applications of mobile, web, or desktop.
Success factors of machine learning in Amazon
The company Amazon utilises the function of Machine learning in their business
model for meeting the requirements of the customers and obtain growth. Machine learning
helped the organisation in several ways for promoting the products in better ways and make
accurate forecasts of sales (Chen et al. 2015). Machine learning provides major advantages
for the sector of marketing and sales, with some of the major benefits as:
ML virtually intake infinite amount of extensive data. The data that is consumed can
be utilised for constantly reviewing and modifying the strategies of sales and marketing on
the basis of the behaviour patterns of customers. As ML consumes data at increasingly high
speed and it identifies the connected data, this function enabled the organisation in
undertaking appropriate actions. The organisation utilises the benefits of machine learning for
analysing the data that is connected with the previous behaviours or the outcomes and then
interpret the data.
Impact of external factors and internal factors
Both the internal and the external factors plays a major role in the IT enabled
innovation in the Amazon Company. The management of Amazon aims on focussing on the
new services and the hardware like kindle e-reader, TV and smartphone, Fire table, Echo that
is powered by the machine learning and Artificial intelligence. Amazon Prime provides
unlimited free shipping and then it is involved in the diversification to new media service
with the access to unlimited constant streaming of the movies and TV episodes (Li et al.
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4USE OF IS/IT FOR INNOVATION
2014). Machine learning helps the company in analysing the data of the behaviours of the
customers and predict what is best suitable for the common public.
The external factors that plays a major role in the success of machine learning in
Amazon is the market of Amazon. With the introduction of machine learning in the business
model of the company, the organisation gained a significant competitive advantage than the
other companies as the analysis of huge amount of data is done in easier method and
techniques (Tramer et al. 2016). The economic condition of several markets helped the
company in developing easily with the implementation of machine learning.
Case study 2: Cloud computing in Netflix
Background of Netflix
Netflix is an organisation that is a provider of media-service situated in Los Gatos.
The primary business of the company is the streaming media that is subscription based and
offers the online streaming of a films and programs of television. The initial business of
Netflix included the sale of DVD and rental by service of mail. The company expanded the
business in 2007 with implementation of streaming media by retaining the rental service of
Blu-ray and DVD. The company expanded the distribution and production of both the
television series and films and provides various content through the online library. When the
service of streaming was launched, the subscribers of the rental disc of Netflix were provided
with access that came at no extra charge. The company implemented the technology of cloud
computing for storing huge amount of data in the servers and provide the services to the
customers on demand (Gupta, Seetharaman and Raj 2013). This technology helped the
company in proper handling the data of the company and secure the data to prevent any kind
of cybercrime that can lead to data loss or data theft.
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Success factors of cloud computing in Netflix
The company implemented the service of cloud for managing the data more securely
and efficiently. Earlier, the data of the company was kept in the local disk of the computer
that did not guarantee the security and integrity of data and this forced the company in
implementing the cloud services in their business model (Chou 2013). For the last two years,
Netflix started the service of providing streaming of video extensively with the help of public
cloud. The company developed several tools internally that are open sourced. By doing this,
the company became the largest video streaming company with the technology of cloud
computing. The Netflix Open Source is the collection of code bundles of Apache that has
been created by the company and have made available to the public. The chief architect of the
cloud of Netflix claimed that the company is progressing towards developing several OSS.
The company is working on establishing the process of Netflix as the best suitable practise of
operating in the public cloud. The company is predicted to gain benefit from the knowledge
of the community of open source and gain improvements (Kavis 2014). The demand of the
common public of television shows and the movies that can be available in the online
platform is increasing at a high rate, which have made the company in managing and storing
huge amount of data that can be provided to the customers whenever required.
Impact of external and internal factors on cloud computing in Netflix
There are some of the internal and external factors that have made the implementation
of cloud computing in the organisation, Netflix successful. The management of the company
aimed at gaining growth by providing services to the customers and the rental video services
of the company helped them as establishing a streaming platform. The implementation of the
cloud computing helped in storing huge amount of data for the common public (Xu et al.
2014). The aim of the organisation of providing services to the customers at lower cost was
successfully executed with cloud computing as the cost of managing a cloud infrastructure is
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minimal and helped in providing seamless streaming service to the customers and make
profit.
Some of the external factors that played a huge role in implementation of cloud
computing was the market of the company (García-Valls, Cucinotta and Lu 2014). The
organisation started out as the DVD rental service for the common people and established
themselves as the best provider. With the increasing demand of the public, the company
explored the sector of streaming services. The company obtained growth in the field with by
providing uninterrupted streaming videos that was facilitated by the implementation of cloud
services in the organisation. The legal condition of some countries put a hurdle on the
company and restricted them from expanding the markets.
Case study 3: Artificial intelligence in Apple
Background of artificial intelligence in Apple Inc.
The company Apple Inc. is a multinational company of technology that performs
designing, developing and selling computer software, online services and electronics for the
consumers. The company implemented the technology of artificial intelligence for creating
development in the products and provide better services to the customers. The company is
promoting the idea of utilising the tools of artificial intelligence by the developers like face
recognition and object recognition and develop the personal artificial intelligence language
Siri for providing better support to the customers (Jha and Topol 2016). The latest technology
of the company HomeCourt uses the machine learning that is added to the operating system
of the mobiles of Apple for analysing any video.
Success factors of artificial intelligence in apple
The strategy of the artificial intelligence in the company, Apple is focused on the
workloads that are running locally on the devices, instead of depending severely on the
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resources that are based on cloud. Even though the technology fits in the business model of
the company, which is selling devices and the emphasis of the company in maintaining
privacy of the data of the company, the developers of the company aims to utilise the full
functions of artificial intelligence for developing better products. The chat bots, virtual
assistants and the robots that are powered by the algorithms of business are extensively being
utilised in the company. The company perform their interview process with the help of
artificial intelligence for managing the screening process efficiently (Markoff 2016). The
main success factor of artificial intelligence in the company is that the capacity of the
company in utilising AI for knowledge gaining and re-using the information and more
accurately, the representation of the knowledge using computers. The information of the
market and the competitors is monitored extensively with the help of AI and then provide
appropriate business plans.
Impact of external and internal factors
There are some internal and external factors on the success of artificial intelligence in
the Apple organisation. The customer support of the organisation is enhanced with the
implementation of artificial intelligence in the business model of the organisation. The
management of the company aims in developing modified and improved products for the
customers that can be created with the help of artificial intelligence (Makridakis 2017). The
advertising of the company is enhanced with the help of AI as the functions of AI reaches the
particular customers and potentially make them customers. The advertisements are provided
to the customers in ways that are relevant to the interest of the customers (Kaplan 2015). The
organisation uses the functions of AI in the platform of social media for developing
personalised and user specific and advertisements.
The external factors that impacted in the success of artificial intelligence in the
company are the technological advances of the company. The basic aim of the company is to
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t provide personalised functions and features that are useful to the customers and help them in
using the devices for better use (Dilsizian and Siegel 2014). The cost of technological
advances in decreasing with time and it can help Apple in implementing more functions of
technological developments for better and personalised use.
Case study 4: Robotics in Mitsubishi
Background study
Mitsubishi is a Japanese companies that are autonomous and multinational. The
company introduced the use of robotics in the company for proper handling of business
functions and gain growth. With the increasingly diversity in the needs of the consumers and
globalisation, the industry of manufacturing is progressing towards developing more
advanced features in the business. Robots in the Mitsubishi company is utilised for
multitasking and perform several tasks with increased efficiency and undertake more
sophisticated tasks that cannot be done by humans. The series of MELFA FR delivers
innovative and solutions that are intelligent that can be used for flexible and advanced
production. The automation needs of the company can be fulfilled with these robots. The
functions of next generation intelligence makes it easy for the companies to function
accurately (Yamamoto 2016). The applications that are safe and collaborative allows the
people and robots in working mutually with increased level of safety.
Success factors of robotics in Mitsubishi
The company Mitsubishi implemented the technology of robotics for gaining benefits.
The main success factor of the implementation of robotics in the company is personalised and
developed production abilities of robotics. With the help of robotics in the company, it
enabled the company in obtaining growth at a significant rate and it also help in proper
managing of change management (Crespo, García and Quiroz 2015). The functions that could
not be performed by the humans are now done easily with the help of robotics in the
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organisation. The efficiency of the company increased at a significant rate as the robots could
perform multitasking at highest levels and the workforce of the company started obtaining
skills for performing tasks that could not be done without the robots.
Impact of external and internal factors
The external and internal factors played a huge role in success of the robotics in the
company. The major internal factor that played an important role was the organisation factor
and the needs of the organisation. The company performs in the sector of manufacturing
industry and the technological developments in the sector creates the opportunity of utilising
heavy machinery and other parts of manufacturing (Tsumugiwa, Fukui and Yokogawa 2014).
The company obtained growth by launching new products that could meet the expectations of
the customers. As the aim of the company is to obtain growth and provide better services to
the customers, the use of robots for effective handling of the heavy machinery is essential as
these machines cannot be operated by the humans (Čermák 2014).
The external factors also played a major role in the success of the company. The
company gained the ability of improved cooperation with the sensors of vision and more
enhanced force sensors that allows increased accomplishment of task that are advanced
(Kober, Bagnell and Peters 2013). The social factors impacted severely on the success of
robotics in the company. The expectation of the customers of having a comfortable drive in
the cars that are designed by Mitsubishi helped the company gain motivation in implementing
the technology of robotics to perform tasks efficiently.
Recommendation
Based on the analysis of the four case studies that are discussed in the report, it is
recommended to the companies to identify the needs of the organisation and plan as per the
needs of the customers. The technological advances has impacted almost every organisation
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in the present times and helped in achieving the business goals quickly. The management of
the organisation should perform analysis of the workshops and the needs of the customer and
use the technological tools for predicting the future needs of the consumers.
Conclusion
Therefore, it can be concluded that the use of IT enabled innovation in the companies
is done extensively for achieving the needs of the organisation quickly. The machine learning
in Amazon offers the wizards and tools of visualisation that guides through the method of
creating models of machine learning without performing the task of learning complex
technology and algorithms of machine learning. The company Amazon utilises the function
of Machine learning in their business model for meeting the requirements of the customers
and obtain growth. Both the internal and the external factors plays a major role in the IT
enabled innovation in the Amazon Company. The management of Amazon aims on focussing
on the new services. The initial business of Netflix included the sale of DVD and rental by
service of mail. The company implemented the service of cloud for managing the data more
securely and efficiently. There are some of the internal and external factors that have made
the implementation of cloud computing in the organisation, Netflix successful. The company
Apple Inc. is a multinational company of technology that performs designing, developing and
selling computer software, online services and electronics for the consumers. There are some
internal and external factors on the success of artificial intelligence in the Apple organisation.
The customer support of the organisation is enhanced with the implementation of artificial
intelligence in the business model of the organisation.
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References
Čermák, R., 2014. Web Camera-based Control of a Mitsubishi MELFA Robotic Arm with
MATLAB Tools.
Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., Xiao, T., Xu, B., Zhang, C. and
Zhang, Z., 2015. Mxnet: A flexible and efficient machine learning library for heterogeneous
distributed systems. arXiv preprint arXiv:1512.01274.
Chou, T.S., 2013. Security threats on cloud computing vulnerabilities. International Journal
of Computer Science & Information Technology, 5(3), p.79.
Crespo, R., García, R. and Quiroz, S., 2015, December. Virtual reality simulator for robotics
learning. In Interactive Collaborative and Blended Learning (ICBL), 2015 International
Conference on (pp. 61-65). IEEE.
Dilsizian, S.E. and Siegel, E.L., 2014. Artificial intelligence in medicine and cardiac imaging:
harnessing big data and advanced computing to provide personalized medical diagnosis and
treatment. Current cardiology reports, 16(1), p.441.
García-Valls, M., Cucinotta, T. and Lu, C., 2014. Challenges in real-time virtualization and
predictable cloud computing. Journal of Systems Architecture, 60(9), pp.726-740.
Gupta, P., Seetharaman, A. and Raj, J.R., 2013. The usage and adoption of cloud computing
by small and medium businesses. International Journal of Information Management, 33(5),
pp.861-874.
Jha, S. and Topol, E.J., 2016. Adapting to artificial intelligence: radiologists and pathologists
as information specialists. Jama, 316(22), pp.2353-2354.
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Kaplan, J., 2015. Humans need not apply: A guide to wealth and work in the age of artificial
intelligence. Yale University Press.
Kavis, M.J., 2014. Architecting the cloud: design decisions for cloud computing service
models (SaaS, PaaS, and IaaS). John Wiley & Sons.
Kober, J., Bagnell, J.A. and Peters, J., 2013. Reinforcement learning in robotics: A
survey. The International Journal of Robotics Research, 32(11), pp.1238-1274.
Li, M., Andersen, D.G., Park, J.W., Smola, A.J., Ahmed, A., Josifovski, V., Long, J., Shekita,
E.J. and Su, B.Y., 2014, October. Scaling Distributed Machine Learning with the Parameter
Server. In OSDI (Vol. 14, pp. 583-598).
Makridakis, S., 2017. The forthcoming Artificial Intelligence (AI) revolution: Its impact on
society and firms. Futures, 90, pp.46-60.
Markoff, J., 2016. Machines of loving grace: The quest for common ground between humans
and robots. HarperCollins Publishers.
Meng, X., Bradley, J., Yavuz, B., Sparks, E., Venkataraman, S., Liu, D., Freeman, J., Tsai,
D.B., Amde, M., Owen, S. and Xin, D., 2016. Mllib: Machine learning in apache spark. The
Journal of Machine Learning Research, 17(1), pp.1235-1241.
Papernot, N., McDaniel, P. and Goodfellow, I., 2016. Transferability in machine learning:
from phenomena to black-box attacks using adversarial samples. arXiv preprint
arXiv:1605.07277.
Tramèr, F., Zhang, F., Juels, A., Reiter, M.K. and Ristenpart, T., 2016, August. Stealing
Machine Learning Models via Prediction APIs. In USENIX Security Symposium (pp. 601-
618).
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Tsumugiwa, T., Fukui, Y. and Yokogawa, R., 2014. Compliance measurement for the
Mitsubishi PA-10 robot. Advanced Robotics, 28(14), pp.919-928.
Xu, F., Liu, F., Jin, H. and Vasilakos, A.V., 2014. Managing performance overhead of virtual
machines in cloud computing: A survey, state of the art, and future directions. Proceedings of
the IEEE, 102(1), pp.11-31.
Yamamoto, I., 2016. Practical robotics and mechatronics: marine, space and medical
applications. Institution of Engineering and Technology.
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