The Need for Big Data and Its Role in Industry 4.0

The aim of this paper is to study big data and its role in operations management. Big data refers to a massive quantity of data or information that is obtained from various sources and can be used by a company or an industry to customize their services and products. The following paper attempts to study the role of big data in Industry 4.0 and the factors that fuelled its rise. Also, a case study of the Ford Motor Company has been provided in the discussion, so as to emphasize the impacts of big data and how it can change the way industries function.

Running head: THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
The need for big data and its role in Industry 4.0
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1THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Executive summary
The aim of this paper is to study big data and its role in operations management. Big data
refers to a massive quantity of data or information that is obtained from various sources and
can be used by a company or an industry to customize their services and products. As such,
big data is a part of the 4th industrial revolution that is currently ongoing. This industrial
revolution has seen the rise and dominance of several new technologies, and big data can be
said to form the foundation for most of them. The use of big data and big data tools would
enable a company to reduce manufacture and production costs, save time, enhance
performance and productivity, optimize customer satisfaction levels and increase revenue
outcome. The following paper attempts to study the role of big data in Industry 4.0 and the
factors that fuelled its rise. Also, a case study of the Ford Motor Company has been provided
in the discussion, so as to emphasize the impacts of big data and how it can change the way
industries function.

2THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Table of Contents
Introduction:...............................................................................................................................3
Introduction to Operations Management and big data...........................................................3
Discussion:.................................................................................................................................4
Role of big data in 4th industrial revolution............................................................................4
An overview of how big data functions.................................................................................5
The need for big data in business operations.........................................................................5
Big data can improve the efficiency and effectiveness of production and services...............6
The benefits offered by big data which can improve effectiveness and efficiency...........7
Case study: Ford Motor Company.......................................................................................10
Big data analytics in supply and demand.........................................................................10
Lessons learnt from Ford’s utilization of big data...........................................................12
Conclusion:..............................................................................................................................12
References:...............................................................................................................................14

3THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Introduction:
Introduction to Operations Management and big data
Management of operations in service and industrial sectors has evolved over the last
few decades, owing to changes in the market requirements. Markets are becoming
increasingly global now, thus forcing enterprises to change their operations management
strategies. Globalized markets, environmental concerns, advancement in technology are some
of the factors that affect operations management at a firm. Moreover, in the past one or two
decades, the internet has completely transformed how businesses acquire and manage the
available resources and data. Operations management or OM has shifted its foundations from
a policy of mass production to that of mass customization (Gunasekaran & Ngai, 2011). As a
matter of fact, big data is believed to be the guiding light, as far as operations management is
concerned.
Big data may be defined as a huge volume of data, in unstructured or structured
formats, which can be used to inundate daily business operations. The 3Vs policy is often
used to describe what big data actually is – the sheer volume of data involved, the variety of
the data and finally the velocity or the speed at which the data is processed (John Walker,
2014). In a business, such volume of data can be obtained from an array of sources, which
include sales records, results from surveys and experiments and so on. The data in question
may be unstructured (like document files), structured (like SQL databases) or even
semistructured. All of this data is expected to be ingested, correlated and analyzed by human
analysts, so as to understand the core essence of such data; the velocity or the speed at which
this data is processed an analyzed forms an integral aspect of big data analytics. The
terminology, “big data” is comparatively new, yet, the process of data acquisition and

4THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
analysis is centuries old. The term garnered international attention only in the early 2000s,
when Doug Laney, industrial analyst, introduced the concept which was to revolutionize
business altogether (Gandomi & Haider, 2015).
In the twenty first century, with growing consumerism and advancement in
technology, the quantity of data that is being generated and accumulated is unimaginable; this
means, that there is tremendous potential for utilizing this data to optimize business
operations. However, the truth remains, only a fraction of this data is actually analyzed
(Chen, Mao & Liu, 2014). The paper below studies the intricacies of big data and its role in
the 4th industrial revolution that is ongoing. Furthermore, the paper also analyzes how big
data analytics could prove to be beneficial for business operations, by increasing productivity.
A case study on Ford Motor Company has also been provided to study the effects of big data
in the industrial sector.
Discussion:
Role of big data in 4th industrial revolution
The twenty first century saw the dawn of what is known as Industry 4.0, or the fourth
industrial revolution, as it is known in common parlance; this industrial revolution has seen
some groundbreaking innovations which include the Internet of Things, artificial intelligence,
quantum computing, cyber physical system and so on (Rüßmann et al., 2015). As a matter of
fact, big data too is an essential component of Industry 4.0 (Lee, Kao & Yang, 2014). With
significant growth in technology, companies (which include ecommerce businesses and even
credit card companies) gather information about their customers (including buying
preferences and tendencies which could be used to enhance customer satisfaction levels in the
future) and store them in databases (Wang et al., 2016). It would be suffice to say that big

5THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
data would be playing a vital role in the ongoing industrial revolution; some analysts have
even claimed that the sole foundation of Industry 4.0 is big data. For example, in the
manufacturing sector, big data is expected to improve efficiency and consequently reel in
billions of dollars in profits (Stock & Seliger, 2016). Similarly, in the financial industry, big
data is what steers and drives the industry today.
As a matter of fact, big data is associated with the other aspect of Industry 4.0, namely
Internet of Things or IoT. In the IoT, the various machines and devices are connected to the
world wide web, through some channel or the other. Along with that, the use of artificial
intelligence makes lives easier and paves the way for newer business opportunities as well.
An overview of how big data functions
Businesses today require timely and efficient analysis of available data, so that the
information obtained can be used to optimize business processes; in the competitive sector
that is business, it is important for enterprises to utilize big data and integrate them into the
production processes. A simple example will help strengthen the point; in the manufacturing
industry, the implementation of Industry 4.0 is expected to change the production processes.
It is assumed that the machines would no longer be dependent on manual labor, instead, they
would be self learning devices that can self diagnose and reduce disruptions in the production
proves (Lee et al., 2013). With the birth of such smart, innovative technologies, the amount of
data and the kind of data generated has undergone a change; this is where big data analytics
comes into play (Dubey et al., 2016). The installation of big data analytics and optimum
utilization of the same would require a sound knowledge of IT domains and data science so
as to decipher the complex programming models and infrastructures.

6THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
The need for big data in business operations
The very term big data refers to a massive quantity of data which cannot be assessed
using traditional or conventional databases and tools. The term does not simply mean the data
in question, it also entails the resources or the tools required to store and analyze this data.
Unfortunately, most companies today lack the resources or infrastructure required to process
such big data (Cukier & Mayer-Schoenberger, 2013). The past few years have seen what is
now known as data explosion; the amount of data available increased from 150 exabytes to
1200 exabytes in a period of five years from 2005 to 2010 (Schrage, 2016). As a matter of
fact, the amount of big data is estimated to increase at a startling rate of forty per cent
annually, which is much more as compared to the rise in population. It is not sufficient to
simply gather this data; big data, in reality, involves curation, search, storage, transfer,
sharing, visualization and finally analysis (Michael & Miller, 2013). This data revolution has
been propelled by the change in pattern of data generation; earlier, it was a simplistic system
where the customer was the consumer of data and the service provider was the source of it.
However, now since most of the devices are connected to the internet in some form or the
other, both the customer and the service provider have become source or consumer of data
(Ward & Barker, 2013).
Big data can improve the efficiency and effectiveness of production and services
The need for big data is not simply because of the sheer magnitude of available data,
but also because of how it can be put to use. The main purpose of data analysis is
multifaceted – time reduction, cost reduction, optimized production and development of new
products (Provost & Fawcett, 2013). The key benefits of big data analytics are:
 It would help determine the root cause of issues, defects and failures in almost real
time.

7THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
 It would analyze the buying habits of the customer and generate coupons on the basis
of that.
 Calculation or risk becomes easier with big data analysis.
 Fraudulent behavior can be identified and eliminated before it causes irreparable
damage.
The benefits offered by big data which can improve effectiveness and efficiency
Using big data can have a number of benefits for a company. Some of them have been
discussed below:
Reduction of maintenance costs
Earlier, the process of replacement of machinery and systems in an organization or
factory was entirely based on estimation and assumptions. For example, it was assumed that a
particular system would wear out after a fixed period of time, and thus it would accordingly
be replaced, even if its life cycle was not over. This was not only inconvenient but also a
costly affair. The implementation of big data would help eliminate such impractical and
costly practices (Lee, Kao & Yang, 2014).
Customer satisfaction
Customers today are quite tech savvy and have critical opinions of their own; they
have their own set of expectations and demands and are not willing to compromise. They
would like to weigh all their options, try out a few brands before settling on a particular
company. As a result, brand loyalty is equally fickle; customers today would not hesitate to
change brands in the blink of an eye. As such, it can be difficult to live up to customer
expectations. However, the use of big data analytics would study customer behavior patterns
and would reveal information about each individual customer’s requirements, buying

8THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
patterns, expectations and so on. This data can then be used by companies to customize their
products to fit the needs of their target customer base (Spiess et al., 2014).
Product reinvention and innovation
Similarly, it is equally important to ensure that the products offered by a particular
company are up to the mark; it is imperative for companies to study how their product is
perceived by the market and what could be done to improve it. For example, surveys may be
carried out by the company to determine customer perception about a product. If the results
of such a survey, as analyzed by big data tools, indicate room for improvement, the company
would be able to make the most of information available to them and reinvent their product,
or their marketing and advertising strategies, as the need be.
Risk analysis
It is a well known fact that any business bears a certain level of risk; the success of an
organization would depend on how a company is able to estimate the risks associated with a
particular strategy or project and adopt adequate measures of eliminating them. Big data
enables predictive analysis, which scrutinizes all available information, to shed light on the
latest developments and trends prevailing in the industry.
Safety and security
Big data would allow an organization to map their entire database, which would
reveal any threats that have pervaded the system, internally or externally. Moreover, such
tools would enable a company to identify sensitive information and the potential threat to
their security; this could go a long way in securing all important data and protect the
company from internal or external breaches, like credit card fraud (Crawford & Schultz,
2014).

9THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Newer revenue streams
The insights that a company would obtain through big data tools and analytics would
not only help in increasing productivity and performance levels but also generate newer
revenue streams. For example, companies could sell the information as non personalized data
to the large players in the same industry.
Enhanced website performance
At present, all companies, big or small will have some kind of online presence; the
availability of big data tools would provide information which could then be used to enhance
website performance. That way, it would leave a lasting impression on the customers visiting
the website. Also, the customer’s personal information, which forms a major portion of big
data, could be used to present tailor mad recommendations which would consequently
improve customer satisfaction levels.
Speedy decision and problem solving
Availability of such information at their fingertips has paved the way for speedy
decision making and problem solving by the companies. For example, a manufacturing
company that is perfectly aware of what their customer expects of them would be able to
better meet the requirements. Similarly, the ability to take decisions faster would hasten the
production process as well.
Incorporation of social media
There has been a lot of hue and cry about the benefits of social media and how it has
revolutionized the industry; but the truth remains, only a handful of companies have been
able to successfully implement social media and ensuing marketing strategies. Big data
makes that easier by allowing companies to track the activity and progress made on social

10THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
media sites. Big data tools especially designed for this purpose would help companies get a
clearer picture of what their customers really want.
Thus, it can be said that big data is certainly the future of the industrial sector; it forms
the pillars of Industry 4.0. As has been mentioned earlier, the amount of big data is expected
to increase in the upcoming years. The need of the hour is for companies to devise strategies
and employ big data tools which can translate the information into critical intelligence.
Without big data, the company would be inviting risks like losing relevancy or missing out on
the latest developments. However, using such big data tools would require some adjustments
in terms of IT infrastructures as well. That could be the reason behind the failure of small
scale firms in employment of big data tools (Jagadish et al., 2014).
Case study: Ford Motor Company
According to Michael Cavaretta, the director of analytics at Ford Motor Company, big
data is too heavy to be processed through traditional systems. The need for driverless vehicles
and the extensive driving research has fuelled the need for big data in the automobile
industry. Ford Australia, Ford Motor Company, is the largest manufacturer and producer of
commercial vehicles, SUVs and passenger cars in Australia ("Ford Australia", 2018). In the
early 1900s, Ford had been the frontrunner as far as the vehicle industry was concerned. But
in 2007, the company faced severe obstacles; by the end of the financial year in 2006, the
company had incurred loss of more than 12 billion dollars. It was during this time that the
company employed big data analytics to revive its operations and change the way
automobiles were manufactured and marketed to the world. By 2009, the company began to
see the light of day once again as they finally began to make profits and even launched
twenty five new vehicles, selling over 2 million cars in on year (Vlasic, 2011).

11THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Big data analytics in supply and demand
The executive team at Ford was aware of what their clients really wanted – they
wanted the right car, with the perfect engine and the exact right features. To cater to each
individual client, Ford came up with a system of Smart Inventory Management System, also
known as SIMS which includes data on the cars sold, the cars manufactured, data on the cars
most searched on company websites, employment rates and so on (Wee & Wu, 2009).
Through a shrewd manipulation of the data obtained, Ford is able to customize their car
specifications and dealership stock. As a result, Ford is able to produce fine tuned cars,
offering multiple options to the customers.
Ford also used big data analytics to monitor and scrutinize posts on social media in
order to understand their customer’s perception about their models. According to Cavaretta,
text mining algorithms were being used which take it one step further than conventional
market research. For instance, manufacturers were in a dilemma as to whether to include a
power liftgate or whether a flip glass system would be used in the new model. The use of
social media tools enabled Ford to simultaneously reduce manufacture costs and improve
customer satisfaction (Bayou & De Korvin, 2008).
Earlier, the cost of manufacturing a prototype exceeded 250,000 dollars; yet, Ford
was releasing nearly 200 prototypes in the case of each product. However, these prototypes
only served the purpose of testing variants, and it was deemed an unnecessary expense by the
company. Thus, they devised the Prototype Optimization Model, which could test the most
number of iterations; this means that the most number of variants could be tested on the least
number of vehicles. The use of such big data tools helped in saving more than 250 million
dollars.

12THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Ford also uses cloud computing, a big data tool which has profoundly changed the
way industries function. Ford had started out with 99 per cent hardware, but has now
optimized its systems to 60 per cent hardware and 40 per cent software (Whaiduzzaman et
al., 2014). In addition, the vehicles manufactured by Ford are now connected to the IoT,
Internet of Things, which has become quite omnipresent now. Cloud computing allows the
company to obtain the data and then store and analyze it, with the permission of the customer.
This data would then be used to determine how a particular vehicle could be improved or
how the customer was utilizing the vehicle.
Lessons learnt from Ford’s utilization of big data
 It can thus be understood that such big data and optimum utilization of big data tools
can help inform design; Ford is able to analyze the existing technologies along with
the ones they expect will make a mark in the future; that is followed by an analysis of
the benefits, the costs involved and other logistics. Such information can then be used
to modify and enhance design of vehicles.
 Ford used social media to understand why the three blink signal feature in Ford Fiesta
was not sitting well with customers. Research into social media responses from
customers showed that the problem rested with the fact that the turn signal was
located on the steering column, which could be fixed easily.
 Ford used big data analytics not simply to reduce costs and improve profit generation
but also to increase the value. For example, the use of tools like Hadoop, has enabled
the company to store data in a cheap and time effective manner. This creates an
innovative data environment where the right information would be accessible at the
right time.

13THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
Conclusion:
In conclusion, it can be said that big data has wholly altered the way industries
function in the present day; big data refers to the wide variety of data that is massive not only
in terms of volume, but also velocity. In manufacturing or other industries, this data would be
pertaining to the customers and minor details about them. For example, it would include a
customer’s personal details, his or her buying preferences, behavioral patterns and so on. All
of this data must be stored and analyzed using adequate tools so as to obtain information
about a customer and to consequently customize service based on the available data.
However, the sheer magnitude of this data makes it impossible for conventional computer
systems to store them, let alone process them. This is where big data tools come into being;
such big data analytics and tools, like social media algorithms or cloud computing would not
only analyze this data but also reduce costs involved in manufacture and production and
improve productivity and performance levels. As was seen in the case of Ford Motor
Company, it was the use of big data tools that rescued the company while it was on the cusp
of decline. Utilizing big data proved to be extremely beneficial for the company; not only was
Ford able to manufacture vehicles or reinvent them using client information but was also able
to include new features, fine tune their vehicles, increase profit generation and reduce
prototype costs. However, it must also be remembered that including big data in operations
management would require a significant shift in infrastructure, which many companies might
not be able to afford.

14THE NEED FOR BIG DATA AND ITS ROLE IN INDUSTRY 4.0
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