Woolworths Case Study: Leveraging Big Data for Business Growth

This case study analyzes how Woolworths, a major Australian retail firm, leverages big data to address various corporate challenges and enhance business operations. The study explores Woolworths' adoption of big data analytics, including automation, in-depth customer insights, and data-driven decision-making. It examines specific issues such as customer preference analysis, product innovation, and marketing strategy improvements. The case study also details the decision-making process, including SWOT analysis and data analytics tools used to gain insights from customer data, transactional data, and web behavior. The aim is to improve customer satisfaction, optimize product lines, and boost overall business performance. The report highlights the challenges faced by Woolworths and how big data analytics has helped them to overcome them.

Big data in solving corporate
problems
Background
There is no doubt that we currently
live in a highly technological universe. For
several decades, the universe as witnessed
huge volumes of data being spawned and
transmitted from one location to another at
extremely high speeds via a wide variety of
tech-based gadgets which include but not
limited to mobile gadgets such as phones
and social media platforms like Facebook
and twitter. The rapid generation of huge
volumes of data led to the development of
the concept of big data several decades ago.
However, the value of big data had not been
realised until recently. Currently, the term
‘big data’ is famously used by a huge chunk
of the world’s populous thus raising the
question, what exactly is big data? Well, big
data is a term that is mostly used when
referring to the massive chunks of raw data
that generally occur in both structured and
unstructured setups and tend to flood huge
business enterprises on a daily basis
(Anthony [1]). Since the definition of big
data lies in the dimensions of the data in
question, it is important to note that any
given data sets can only be referred to as big
data if they tend to present the extreme
degrees of volume, velocity, variance, value
and veracity.
At this point in time, the value of big
data is clearer than ever thus, a huge chunk
of well-established and upcoming businesses
have developed an appreciation for the value
of big data and therefore, across the world,
business are actively trying to come up with
different ways and means of capturing all
forms of data that stream into their
operational cycles on a daily basis.
Basically, the huge need for big data is
driven by the fact that data plays an
enormous role in developing prized
awareness revolving around targeted
demographics and general client inclinations
with regard to different products and
services (Daniel [2]). Several noteworthy
studies such as the Gartner report of 2019
have revealed that from every technological
interface, regardless of whether it occurs in
active or passive manner, the general
populous is essentially creating new forms
of data that can be helpful to different
business enterprises. As such, every single
second data is essentially being netted
through several mechanisms which include
but not limited to video cameras, credit
cards, computers, web platforms and cell
phones. However, it is important to note that
big data can only generate meaningful
insight if analysed accurately and in the
correct manner using the appropriate data
analytics tools such as Apache and Hadoop
ecosystem software.
Issues that Woolworths has
tackled using big data
Woolworths Limited is one of the
biggest retail firms in Australia, having
incorporated several renowned brands which
include Woolworth’s chain of Supermarkets,
BIG W, Dick Smith Electronics and Dan
Murphy’s. At the moment, Woolworths is
actively seeking to diversify its business
operations and acquire more companies
(Nigel [10]). In this regard, Woolworths
Limited has made a pledge to do all it can so
as to foster progressive enhancements and
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growth across all its operational divisions.
Big data undoubtedly tends to generate a
copious volume of new development
opportunities ranging from internal insights
to front-facing customer interactions.
Woolworth’s employs business analytics at
a mega scale with a goal of analysing their
clients’ shopping habits and preferences.
With a goal of gaining independence with
regard to big analytics, Woolworths is
reported to have spent an approximate figure
of $20 million dollars to buy stakes in data
Analytics Company. At the moment, nearly
1 billion is being spent on analysing
consumer spending habits, and boosting
online sales. As a result of these efforts,
some of the key business opportunities that
have been generated so far include the total
automation of all business operations, in-
depth customer insights acquisitions and
general data-driven decision making
(Hsinchun & Storey [6]). More specifically,
Woolworths is currently seeking to
introduce a new line of products in all their
retail outlets. In regards to this endeavour,
Woolworth is deploying the benefits of big
data analytics in the following ways:
 Automation
Basically, big data has the
exponential potential to enhance the internal
competences and operations of Woolworths
via several robotic automation processes. At
the moment, enormous volumes of
instantaneous data are being analysed on a
real-time basis and built into meaningful
business procedures that have always proven
to be very helpful in the decision making
process with regards to the issues such as
customer satisfaction and introduction of
new product lines. Woolworths is currently
able to apply big data analytics within its
operational budget due to the easily
accessible Information Technology
infrastructures and the ever declining cloud
computing-related costs that have made the
automation of data collection and storage
easier (Seref & Sinanc [12]) .
 In-depth insights
At Woolworths, big data is currently
being used to ascertain the most viable
opportunities with regard to the beauty
products market that were previously
unfamiliar to the firm before the advent of
the capabilities of big data and big data
analytics as tools for decision making.
Complex data sets are being used to develop
and source for a new line of beauty products
while at the same time setting up measures
to improve the existing products. With no
doubt, I can say that proprietary data within
the market has proved to be of extreme
value to Woolworths.
 A quicker and smoother
decision making process
Due to the swiftness of data analytics
technologies compounded with the ability to
analyse new sources of data accurately,
Woolworths is in a position to analyse the
available raw data in an accurate and instant
manner and as such, use the insights
obtained from the data analysis to make
smart and well informed decisions.
Before Woolworths started using big
data and big data analytics, they were facing
several problems ranging from the sluggish
consumer cycle and the diminished market
growth rates. These problems led to shift of
consumer focus towards fresh foods and
broader grocery categories, which did not
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seem to be positive at all. Looking back at
how things stood then, there is no doubt that
Woolworths problems arose as a result of
the extreme lack of product innovation and
creativity compounded with the fact that the
company was not able to communicate with
all its stakeholders appropriately.
Furthermore, their customers were largely
unsatisfied. Before the advent of big data
and big data analytics there was a very clear
lack of incorporation of any meaningful
marketing communications strategy at
different levels of Woolworth’s
organizational chains.
Issues affecting the Woolworth
supermarket
The Woolworth supermarket is
trying to establish its client base and
preference using big data by collecting data
form it users shopping cards basing on the
loyalties. The data to be acquired from the
shoppers includes:
 Data concerning the
products usage and the services
offered.
 Customer web
behaviour data.
 Transactional data.
 And data containing
consumer preference.
The Customer data analytics refers to
the procedure of gathering and afterwards,
examining customer data in order to study
customer conduct and preferences which are
then applied in making business-related and
strategic decisions (Chiang & Storey [5]).
The supermarket board of directors is
aiming at collecting this data, which should
be analyzed using proper decision making
tools and to make best decision at will be
effected by the end of the year. The data
collection process will be easier to the
supermarket since it will be using only data
sourced from its clients. However, it will
pose a threat to the organization since it will
be infringement of people privacy data to
use their information without letting them
know. It is recommended that the
organization should inform the people and
its clients the reason for their need to use
their data and to seek their approval.
To solve the marketing issue, the
data to be sourced needs to be divided into
four main occupational analytics that are
instrumental in analyzing it: descriptive,
diagnostic, predictive and finally the
prescriptive data analytics.
Descriptive; this data analytic part
deals with what had happened previous, the
reason and the real motivation that drove the
need to conduct this data processes. For this
Woolworth organisation, the need to
conduct this study arises with the need to
analyse consumers’ data to determine if
adding new a line of product will be
instrumental basing on the growing concerns
(Habersang, & Seckler [11]). The main
motive behind this development is the
supermarket goal to continuously grow and
this was hampered will resulting reducing
profit since the year 2017 when they were
the leading organisation in the Australia.
Potential questions include:
 Is there a need to
increase market pool?
 What do will need to
do to stop the reoccurring of what
happed to profits in the year 2017?
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Diagnostic; this data analysis is
focusing on the reason for conducting this
process and as to why internal data is used.
Internal sources of data is used in this study
because it is aimed at making decisions for a
single organization hence only its own data
proved to be more instrumental in making
decision pertaining the wellbeing of the
organization at large (Mohsen, and
Gunasekaran [8]). Potential questions
include:
 Do we have enough
data for this process?
Predictive; this predictive data is the
most significant analysis in this phenomena
of big data analytics since it provides
insights of how the data will be looking like
and the numbers it will represent. It should
be noted that the numbers developed by this
predictive analysis are not the actual figures
and are just mere speculations and close
representation of the actual figures (Ewa,
[4]). This is actually important to the
Woolworth management has it gives them
an opportunity to get prepared for the
decision that can be arrived in the course of
the decision making tools. It was forecasted
clients of the Woolworth supermarket
clients will allow the supermarket
authorities to use their data and that their
shopping data will be in favor of the
supermarket introducing the new line of
products. Potential questions include:
 Will the Woolworth
supermarket clients allow the
supermarket authorities to use their
data and that their shopping data will
be in favour of the supermarket
introducing the new line of products?
Decision making
Steps of the Decision-Making
Process
 Classify the decision.
 Collect relevant info.
 Ascertain the
alternatives.
 Weighing the
available evidence.
 Choosing one
decision among the alternatives
present.
 Taking necessary
action.
 Reviewing the made
decision to ascertain if it relevant.
Decision making flow chart
Decision making tool
Decision making is usually a crucial
but complicated process especially when
making decision is tasked to board of
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directors. The board will face rough times
since they have to consider all aspects to so
as to decide to go for the new decision or to
simply ignore and wait for the best time to
go for it. The Woolworth supermarket is a
large organization of chains stores spread
unevenly across the globe. Here in Australia
it is the leading groceries distributer. To
make a decision that will affect the running
of such a great organization proofs to be
difficult since it has to be correct. To make
the best decision it necessary that the board
uses big data decision making tools to
achieve the best goal
SWOT Analysis
SWOT is an abbreviation which
stands for strengths, weaknesses,
opportunities and threats which are the key
elements to consider when making a
decision as discussed below:
 STRENGTHS-
focusing on the strengths, data is
observed in projections for
understanding that whether
introduction of the new line of
product will have the capability of
building strengths to the organization
in terms of more profits and to earn
the company more clients.
 WEAKNESSES-
similar to strengths, focusing on the
weakness, focusing on the
weaknesses, data is observed in
projections for understanding that
whether introduction of the new line
of product will have the capability
exposing the company in terms
reducing profits which can further
cultivate into losses, wastage of time
and employee incapacitations (Emet,
and Tat [3]).
 OPPORTUNITIES-
these are the simple chances that
present themselves in the aura of
launching the new line of products
which do include; increased income,
fetching of new markets, enjoying
economies of scales due to market
size expansion among others.
THREATS- these are the
pretentious obstacles that present
themselves in the aura of launching the
new line of products which do include;
insufficient funds, investment fears,
incapacitate employees who might need
retraining, increased risks and hazards.
The advantage of venturing into a
new line of products is that it will enable the
supermarket to increase its sales pool,
employment pool and definitely profits
increase thereby moving to the next level
while the disadvantage facing it is that it will
pose investment risks to the supermarket.
On the other side the advantage of not
investing is that nothing will at risk while
the major drawback is that there is nothing
to be earned either.
Recommendation and time
framing
The board of management is tasked
with making the decision with more
strengths and opportunities as opposed to
one with more weaknesses and threats. To
achieve this goal, it recommended that the
data should be collected for a period of six
month, analyzed for three months and
decision is made before the end of the year
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while the board makes speculation using the
predictive data.
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