Use of IS/IT for Innovation: Case Studies of Amazon, Netflix, Apple, and Mitsubishi

Running head: USE OF IS/IT FOR INNOVATION
USE OF IS/IT FOR INNOVATION
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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

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

3USE OF IS/IT FOR INNOVATION
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.