Information Systems | Assignment

Running Head: IT 0
INFORMATION SYSTEMS

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Solution 1)
Industry revolutions are momentous events and it is stated by Geissbauer, (2016), that
the fourth industrial impelled by unified digital technology rapidly transforming many
companies and industries at large. In simple words, Industry 4.0 talk about to the combination
of some of major innovations in digital technology joint together so that to integrate physical
world with the virtual world. This transformation and change enable a great new way of
managing international actions and processes, carrying the compatibility and software speed
to wide scale manufacturing of machines. Businesses that hold Industry 4.0 are started to
track each and everything they create from cradle to grave and therefore, enables mass
customization for the customers in terms of products and services (Xu, Xu & Li, 2018).
The movement of Industry 4.0 was started back in Germany considering their great
initiatives and this movement is currently reflected prospects of rapid payoffs in corporate
results. One of the significant transformation carried by Industry 4.0 is the replacement of
legacy systems and as a result, brings out greater technological integration as well as
efficiency. Some of the digitalization benefits of Industry 4.0 includes complete digitalization
of a business operations, products and services redesign and close interaction with
consumers. According to Geissbauer, (2016), Industry 4.0 entails openness’s with
information and partnership to be work as a globalised accelerator and help the companies to
gain more potential customers.
The web of technologies that are involved in Industry 4.0 includes the internet of
things (IoT), cyber physical systems, smart manufacture, smart factories, cloud computing,
artificial intelligence and cognitive computing. All these technologies can form virtual sorts
of real-world installations, applications and processes and consist of interconnectivity amid
processes, information transparency and technological support for dispersed decisions. In
simple words, it allowed a greater digital transformation while joining up the systems and
alterations though business models. Elijah et al (2018) defined the IoT as a system of unified
computing devices, systems, individuals and digital machines with distinct identifiers and the
capability to transfer data over a network without need of person-to-person or person-to-
machine interaction.
The next technology is cyber physical systems that are transforming the way people
interacts with engineered systems with controlling physical process and through feedback,
adapt itself to new circumstances, in real time (Lee, Bagheri & Kao, 2015). In smart

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manufacturing, everything is connected with the aid of RFID chips and sensors and a key
component of smart manufacturing is decentralisation control. Similarly, the smart factories
is also a part of Industry 4.0 that represents a leap forward from more conventional
automation to a complete flexible and connected system and this can basically change
production processes and improve relationships with customers and suppliers (Stock &
Seliger, 2016).
One of the biggest evolution of industry 4.0 is cloud computing technology where
different sorts of computing services can be stored and accessed over the internet instead of
through physical hard drives. Cloud computing is using different segments such as SaaS,
PaaS and IaaS and according to Liu (2020), the storage, hosting and computing cloud
services market was projected to be 126 billion U.S. dollars in 2017 and was estimated to rise
to 163 billion U.S. dollars in 2021.
In similar to cloud computing, artificial intelligence is also one of the great evolution
representing wide array of applications comprising robotic process automation, machine
learning and natural language processing. Tractica (market research firm), the international
AI software market is predicted to experience huge growth in the upcoming years with
income rising from near10 billion U.S. dollars in 2019 to an projected 126 billion by 2025
(statista.com, 2020). At last, cognitive computing technology under Industry 4.0 process uses
a blend of machine learning, artificial intelligence and natural language processing at a b
scale.
There is a significant impact of these Industry 4.0 technologies on business process
and performance as with investment in these technologies, businesses and manufacturers can
become more agile, efficient and collaborative than ever before. This help manufacturers to
develop new, more productive and innovative business models and therefore, help in creating
a new ecosystem of industry partnerships (Dalenogare et al, 2018). With artificial intelligence
and cloud computing, the system gains and analyse new data with optimising whole
production process, resulting in lower lead times and energy consumption. Business
performances automatically increase as there is reduction in the number of human workers
and machines and systems are known for their accuracy characteristics.
These industry 4.0 technologies help the business to establish a more connected
workforce that helps the company and management to streamline the processes so that
productivity can be raised as much as can. These technologies also help the business in

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improving their business performance while adapting it to the external market conditions with
greater flexibility and therefore, ensure that the business can develop better agility and speed
in response to the consumer needs and external business environment (Haseeb et al, 2019).
Business performance also increases when the business scale up to a wide platform and this
can be facilitated through cloud computing technology of Industry 4.0 and it also helps the
business to create better control over data files.
Solution 2)
It is true that small businesses have to mount up various types of data like financial
information in relation with expenditures and income, employee’s data, customers and
supplies. However, using traditional file management system is no more beneficial due to
increasing competition from big scale companies and this requires them to get updated in
times to keep the standards in accordance with technological developments. In the case of
Bob who is the owner of small auto mechanics business and using spreadsheets and a paper
based filing system for storing the information, there is need to implement a new system such
as Workflow Management System.
In an effort to embrace automation inside the workplace and offer a unique customer
experience, Bob can implement this system to manage the business process most effectively
while scaling up productivity. Nunhes et al (2017) defined workplace management as the
system that aid in creating and optimising the paths for data and information to complete
items in a definite process. In simple words, it helps in streamlining day to day business
processes for optimal efficiency. Some of the major functions of workflow management
include – form modelling, document integration, report generation, user assignment, role
based accessibility, cloud omnipresence and email notification.
Bob will receive many benefits when successfully implementing workplace
management as it helps his business in streamlining and speed up internal processes such as
finding which employee was doing the respective work so as to better align task with the
skillsets and presents a unified, personalised request experience for all 3 employees. It will
also help Bob to typically prepare the purchase at the right suppliers. Workplace management
system will also help his business in drastically reducing the paperwork and associated costs
and waste. This will directly help in risks of improperly approved requests from the clients,
hires or any sort of contracts. Furthermore, this system will also help in tracking and

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improved communication and also increase the visibility to keep the everyday operations
running smoothly.
To design workplace management system, there are some systems development
activities that must be undertaken in sequential order such as system analysis, system design,
programming, testing, conversion, production and maintenance (Laudon and Laudon, 2018).
In system analysis, the problem will be analysed which I try to solve with an information
system. It includes describing the challenges, recognising causes, stating solutions and
therefore, accordingly develop the road map. This phase also includes a feasibility study from
my side so that to come up with best or alternate solution to the problem. Here, the problem is
to how make track of customers, supplies and employees and how to automate the process so
that to automatically send the reminders to the customers when their car service is due.
The next phase will be system designing where I have to develop a model of
workplace management system in reference to a blueprint so that effective system can be
developed fulfilling the objectives. At this stage, I have to hire professionals to present details
for the system specifications that will be developed during system design. At the next step, it
needs to ensure that right programming of the system will be taken out by specialists or
professionals in terms of software program algorithms and codes. I can also look for the
vendor solutions in the market that best suited for the business.
Testing will be the next phase in which I ensure that the developed program is
working well and error free and whether discrepancies exist amid the way the system
essentially works and the way it was conceived. After testing, conversion will be done refer
to moving from the old system to the new system with undertaking four key strategies i.e.
parallel strategy, straight cutover strategy, pilot study strategy and phased approach strategy.
Ultimately, the last stage will come signifying maintenance and production, where the new
system will successfully be implemented for Bob small auto business and at this phase, the
system will continuously be monitored by specialists so that it can be modified when needed.

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References
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected
contribution of Industry 4.0 technologies for industrial performance. International
Journal of Production Economics, 204(1), 383-394.
Elijah, O., Rahman, T. A., Orikumhi, I., Leow, C. Y., & Hindia, M. N. (2018). An overview
of Internet of Things (IoT) and data analytics in agriculture: Benefits and
challenges. IEEE Internet of Things Journal, 5(5), 3758-3773.
Geissbauer, R. (2016). Framework for Evaluating Supply Chain Execution Systems.
Retrieved from https://www.strategy-business.com/article/A-Strategists-Guide-to-
Industry-4.0?gko=a2260
Haseeb, M., Hussain, H. I., Ślusarczyk, B., & Jermsittiparsert, K. (2019). Industry 4.0: A
solution towards technology challenges of sustainable business performance. Social
Sciences, 8(5), 154.
Laudon, K.C. and Laudon, J.P. (2018). Management Information Systems: Managing the
Digital Firm, Global Edition, 15th Edition. England Pearson (Intl).
Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for industry
4.0-based manufacturing systems. Manufacturing letters, 3(1), 18-23.
Liu, S. (2020). Cloud Computing - Statistics & Facts. Retrieved from
https://www.statista.com/topics/1695/cloud-computing/
statista.com (2020). Revenues from the artificial intelligence (AI) software market worldwide
from 2018 to 2025. Retrieved from
https://www.statista.com/statistics/607716/worldwide-artificial-intelligence-market-
revenues/
Nunhes, T. V., Barbosa, L. C. F. M., & de Oliveira, O. J. (2017). Identification and
analysis of the elements and functions integrable in integrated management
systems. Journal of Cleaner Production, 142(1), 3225-3235.
Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry
4.0. Procedia Cirp, 40(1), 536-541.

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Xu, L. D., Xu, E. L., & Li, L. (2018). Industry 4.0: state of the art and future
trends. International Journal of Production Research, 56(8), 2941-2962.