Introduction.
People in business administration are interested in improving the operations of companies.
Increasing customer satisfaction, reducing cost of doing business, and establishing new
products and services at low cost are important aspects of business process management from
a business administration point of view.
Enterprise process management, also known as business process management, is a method
that organises and implements all of the activities in an organization in a structured way. This
aligns them with organizational goals and maximizes integration across different functions
and processes. It is based on the observation that each product that a company provides to the
market is an outcome of a number of activities performed (Weske, 2007).
An enterprise is expected to not only be effective and efficient but also be able to adapt to the
frequent changes in the market environment driven by technology, regulation, and
competition. And for enterprise/ businesses to be able to do this, tools, different methods and
techniques emanating from information technology industry have a tremendous impact on the
very nature and operations of enterprise.
Functions supported by EPM systems include accounting, manufacturing, human resource
management, purchasing, inventory management, inbound and outbound logistics, marketing,
finance, engineering, customers and general public. The systems include MRP, MRP 11,
ERP, ERP 11. Extended Enterprise Systems Framework (EES) concept is based on EPM,
primarily build on the notion of the process as the central entity. EES include tools to manage
processes, design, execute and evaluate processes and redesign processes in real-time.
EES has four distinct layers: a foundation layer which provides a platform for the EES
system, a process layer which is central component based on business process management
and enterprise resource planning, an analytical layer which has components that enhance
central ERP functions like supply chain management, and an electronic business layer which
has collaborative components that connect the system to actors like customer, business
partners, employers, and even external systems.
Background on Industry 4.0
As Park (2016) puts it, industry 4.0 involves the transformation of entire systems across
countries, companies, industries, and society as a whole.
Technologies such as artificial intelligence, the Internet of Things (IoT),
cloud computing, social media, data science, 3D printing, connected
wearable devices, quantum computing, robotics, and genetics are the
driving forces of this Revolution.
These transformative technologies will impact all disciplines, economies,
businesses, societies, and individuals. Do & Pendrell (2020) strongly claim
that industry 4.0 will blur the boundaries between physical, digital and
biological worlds. According to Schwab (2017), physical world include
autonomous vehicles, 3D printing, advanced robotics and new materials
like grapheme, polyhexahydrotriazines. The digital world includes sensors
and accessories, transmitter or radio frequency identification, block chain.
Biological world include genetics, cancers etc.
First industrial revolution happened in the late 1700s with the advent of
steam power, mechanisation and the invention of the weaving loom as
such a factory was born.
The Second industrial revolution happened approximately 100 years later
when electricity, mass production and the assembly line transformed the
way we lived. This led to mass consumerism.
The Third industrial revolution involved automation, computers and
electronics. It began in the mid-1950s with the creation of general-
purpose computers. Miniaturization led to computers entering people’s
homes.
Klaus Schwab (2017) claims we are witnessing profound shifts across all industries, marked
by the emergence of new business models, the disruption of incumbents and the reshaping of
production, consumption, transportation and delivery systems. On the societal front, a
paradigm shift is underway in how we work and communicate, as well as how we express,
inform and entertain ourselves. Equally, governments and institutions are being reshaped, as
are systems of education, healthcare and transportation, among many others. New ways of
using technology to change behaviour and our systems of production and consumption also
offer the potential for supporting the regeneration and preservation of natural environments,
rather than creating hidden costs in the form of externalities.
Ulrich Sendler states that Industry 4.0 began in 2010, and a term was coined in 2011 at a
Hannover Fair, as a future-oriented project, stemming from the high-tech strategy of the
German federal government. It stands for the fourth industrial revolution, a new level in
organizing and controlling the continuous value creation chain over the entire lifespan of
products. It focuses on an increase in flexibility of production, based on individual customer
wishes. Its foundation is the availability of all necessary information in real time, in order to
optimally steer the value stream, leads to the integration of production materials, components
and employees into the networking and communication system.
Canals & Heukamp (2019) summarized it in the preface of their book as the current
technology revolution is reshaping industries, disrupting existing business models, making
traditional companies obsolete, and generating social change and anxiety. the emerging new
world of big data that empowers Artificial Intelligence (AI) is redefining some basic
principles on decision-making in organizations, and has the potential to make organizations
simpler and leaner, and change the general manager’s tasks. AI has led to collection of more
abundant data and development of sophisticated algorithms that help make complex decisions
of predictive nature and leading to automation in many business’ processes. It is transforming
industries like retail, fashion and financial services in using this abundant data to develop
new marketing and sales strategies to approach the final customer. Some AI new tools are
improving managers’ capabilities to make predictions, a very important dimension in
different business functions, such as manufacturing, purchasing, sales, marketing, or logistics.
This bigger and better prediction capability is opening up interesting possibilities for
companies, encouraging firm creation, redefining business models, challenging companies
and management, and making traditional corporate strategies out-dated.
Human decision-making is imperfect and subject to cognitive biases and gaps in rationality
that can lead to suboptimal decisions. AI can be used here to enable human-agent team to
collectively perform cognitive tasks better than human or software agents alone. The system
helps decision makers to effectively interact with a large amount of information using speech,
gesture and data visualization techniques.
In product marketing domain, AI can measure customer sentiment and track buying habits for
sales and marketing which is used by brands and advertisers in making ecommerce more
intuitive and for targeted promotions. AI creates more personalized and improved
communications to prospects and customers. AI will also expand workforce management
applications into recruiting and hiring, managing employee turnover, and ensuring employee
growth and satisfaction. AI models will also be able to tap into data within the organization to
guide employees in developing skills and pursuing opportunities to grow within the company.
Several key management functions, such as human resources, recruitment, and decision
support systems, have already benefited from applications of AI technology. An example is
IBM’s Watson solution that helped Woodside, Australia’s largest energy company to retain
knowledge of senior expert and management.
Organizations will be able to use these AI models to increase operational efficiency, make
more informed decisions, and innovate faster to create new products and services.
The Internet of Things, also known as IoT describes any object that is connected to the
internet but can also talk to eachother. Examples include smartphones and smartwatches.
Artificial intelligence is a computer system able to perform tasks normally requiring human
intelligence. Do & Pendrell (2020) give an interesting examples of how AI in being used in
medical diagnostics. Goggle’s DeepMind makes 94.5% correct diagnosis of eye problems. AI
is also at the core of self-driving cars which many car manufacturing are actively exploring.
Lucini & Serina & Susannah (2020) cite an example of how Intelligent Growth Solutions
uses AI to enable indoor farming and how Hyundai creates iron man suits that provide extra
strength to factory workers lifting heavy objects.
Augmented reality (AR) superimposes a computer-generated image onto a real world
situation. It used by US Army in development of programs to help distinguish between
enemies and friendly troops in combat.
3D printing turns a digital model into a physical three-dimensional object by squeezing a
liquid material through a movable nozzle. This is contrast to the current mode of doing
things, subtractive manufacturing where layers are removed from a piece of material until the
desired shape is obtained (Schwab, 2017). NASA is exploring use of this technology to print
starch, protein and fat which would have a longer shelf life than conventional pre-packaged
space food and could dramatically reduce storage space and subsequent waste.
Genetic engineering. Gene editing is a type of gene editing in which DNA is inserted,
deleted, modified or replaced in the genome of a living organism. This differs from genetic
engineering practiced in the 1980s in that it is much more precise, efficient and easier to use
than previous methods. It has been used by researchers of John Hopkins to engineer
mosquitoes resistant to malaria parasite. Gene engineering when combined with 3D printing
is called bio printing and has been used to generate skin, bone, heart and vascular tissue.
Fourth industrial revolution has been immense. The World Wide Web has enabled
globalisation and outsourcing, radically changing the way individuals and companies interact
with each other and as such small companies are now able to access much larger markets than
ever before.
There has been democratization of knowledge where acquired knowledge is spread amongst
everybody not just the privileged.
Employability. Job seekers must go beyond the basic digital skills.
Society, schools are using closed social media platforms such as Edublogs to share and peer-
review works.
Profiling where people are covertly targeted for bespoke political campaigns. Documentary
‘the Great Hack’ explores how social media can be used to influence political systems.
Automation that is part of industry 4.0 has significantly impacted the job market, with some
skills and roles already becoming redundant such as job of checking attendance of staff in
hospitals and students in schools like Mengo Senior School. Cambridge University is
considered ending the 600 year tradition of handwritten exams by allowing entrants to type
answers on a laptop.
Do & Pendrell (2020) assert that 90% of all the data throughout history
has been generated in the last two years. This big data is in healthcare,
entertainment, finance, education, retail and manufacturing. Industry 4.0
makes this data to be analysed quicker and with greater accuracy.
Crowdsourcing has revolutionized traffic conditions and other live
information about road congestion hence allowing individuals to choose
alternative routes and it is used to tackle street harassment in Egypt.
Anderl et al summarises it as a new level in organizing and controlling the continuous value
creation chain over the entire lifespan of products. I will consider how Industry 4.0 with its
related technologies supports the Enterprise Management process.
- Coordinating activities by help to drastically reduce on the cost of coordination within
and between firms. This also helps in creating a paperless quality assurance
- Making decision where Industry 4.0 technologies make more and more accurate
judgements. Interoperability, maintainability and extensibility, testability, portability,
scalability, flexibility, usability, availability, reliability, maintainability, performance,
time to market, cost and lifetime. For example cloud computing gives EPM system
the benefit of flexibility and resiliency and reduced cost in terms of software licensing
fees, hardware costs, provisioning expenses, energy costs etc. cloud computing offers
not only a centralised data storage but also a larger amount of data storage resources
than conventional systems and this in turn deceases or increase in the resources used
per requirements which adjusts operating costs. Also data protection mechanisms are
much easier to implement and monitor in a centralised system. Reduced time to
deployment as it offers the means to use powerful computational or large storage
resources on short notice.
- Defining objectives. Design quality products and services by understanding customer
needs and translating them into product and service specifications.
- Motivating employees. AI technologies makes it possible today to monitor and
evaluate how well individuals are performing specific tasks in real time. This data
when analysed
Much as Industry 4.0 is immensely changing the world as we know it. It is without problems
of its own. For IoT, anything connected on the internet can be hacked. AI has raised issues of
transparency, responsibility and discrimination. For example Twitter’s experimental AI was
deactivated only hours after launch due to, ironically, it’s learnt racism. AR has been noted to
be distractive and may cause a potentially dangerous situation such as Pokémon GO was
blamed for contributing to nearly 150,000 traffic accidents and 256 deaths in its first 148 days
of its release. 3D printing has led to production of unregistered weapons. Klaus Schwab
further highlights that Fourth industrial revolution will exacerbate economic inequality, on
the side of work and production with decline in the share of labor as a percentage of GDP and
because the great beneficiaries of the revolution are the providers of intellectual or physical
capital.
References
Anderl, R., Anokhin, O., & Arndt, A. (Efficient Factory 4.0 Darmstadt—Industrie 4.0
Implementation for Midsize Industry.
Do, T. & Pendrell, S. (2020). Learning about current digital workplace trends. University of
Leeds. Retrieved April, 09, from www.futurelearn.com.
Park, H.-A. (2016). Are we ready for the fourth industrial revolution. IMIA and Schattauer
GmbH.
Klaus Schwab. (2016). The fourth industrial revolution. World Economic Forum. Crown
Publishing Group. New York.
Lucini, F., Serina, A., & Susannah, M. (2020). Digital skills: Artificial intelligence; week 2:
artificial intelligence in industry. Accenture. Retrieved April, 13, from www.futurelearn.com.
Mathias Weske. (2007). Business Process Management: Concept, language, architectures.
Springer. Berlin.
