Countdown Supermarket: A Global Information Strategy Evaluation

This report provides a comprehensive analysis of Countdown Supermarket's global information strategy. It begins with an introduction to Countdown, outlining its mission, corporate structure, major business processes, and business strategy. Part 2 delves into Countdown's IT infrastructure, including hardware, internet platforms, database management, mobile platforms, and enterprise software planning. It also examines the issues and challenges in managing IT infrastructure, such as lack of computing power, data acquisition problems, and poor network connections. The report then explores the adoption of emergent technology, along with recommendations and challenges related to artificial intelligence. Part 3 focuses on big data, defining its potential, and discussing the Internet of Things, cloud computing, and big data analytics applications in business. It covers business opportunities, problems, and the future of big data, along with a big data strategy, including key areas of impact, risks, and supporting tools. Finally, the report concludes with an overview of the key findings. The report showcases how Countdown leverages technology to enhance its operations, customer service, and overall market position.

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GLOBAL INFORMATION STRATEGY
Name of student
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Table of Contents
PART I.............................................................................................................................................4
1. Introduction.................................................................................................................................4
Background..................................................................................................................................4
Mission.........................................................................................................................................4
Corporate structure......................................................................................................................4
Major business processes.............................................................................................................5
Business strategy..........................................................................................................................6
Relationship with external entities...............................................................................................6
Countdown homepage URL.........................................................................................................7
Part 2...............................................................................................................................................7
2.1 IT infrastructure.....................................................................................................................7
Hardware platforms.................................................................................................................7
Internet platform.......................................................................................................................7
Database management and storage.........................................................................................7
Mobile digital platforms...........................................................................................................7
Enterprise software planning...................................................................................................8
2.2 Issues and challenges in managing IT infrastructure............................................................8
Lack of powerful computing equipment...................................................................................8
Problems of acquiring data......................................................................................................8
Lack of efficient data storage...................................................................................................9
Poor network connections........................................................................................................9
Computing management...........................................................................................................9
2.3. Adoption of emergent technology.........................................................................................9
Recommendations for new technology...................................................................................10
2.4 Challenges of artificial intelligence.....................................................................................10
Part 3.............................................................................................................................................11
3.1 The definition of big data.........................................................................................................11
The potential of big data................................................................................................................12
Internet of things for big data analytics.....................................................................................12
Cloud computing........................................................................................................................12

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Uses of big data analytics in business...........................................................................................13
Decision making.........................................................................................................................13
Quality management and improvement.....................................................................................13
Business opportunities and benefits of big data............................................................................13
Predictive analytics consultancy................................................................................................13
Fashion trends analysis and forecast.........................................................................................14
Problems of big data analytics......................................................................................................14
Storage and analysis..................................................................................................................14
Security of information...............................................................................................................14
Future of big data..........................................................................................................................15
Server-less architecture.............................................................................................................15
3.2 Big data strategy......................................................................................................................15
Reason for investing in big data................................................................................................15
Key areas of impact.......................................................................................................................15
Customer intelligence................................................................................................................15
Quality improvement..................................................................................................................16
Risks to consider and mitigation................................................................................................16
Mitigation...................................................................................................................................16
Supporting tools and skills needed.............................................................................................16
Measurement of success................................................................................................................17
Increased customer information................................................................................................17
PART 4...........................................................................................................................................17
4.1 Conclusion...............................................................................................................................17
Bibliography..................................................................................................................................19

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PART I
1. Introduction
Background
Countdown supermarket is the leading brand in New Zealand with more than 3 million
customers buying products every week. The supermarket operates in the retail industry that deals
with food such as grocery and animal produce. Countdown is a subsidiary of Woolworths New
Zealand, which is an extension of Australia’s Woolworths. Being a subsidiary of Woolworths,
Countdown has enjoyed benefits such as experienced managerial expertise and wide market
share belonging to the parent company. Therefore, Countdown New Zealand has enjoyed much
success in the market to become a leader in the retail industry.
Key products
Countdown supermarket deals with,
1. Fresh grocery
2. Chilled and frozen food
3. Seafood
4. Meat products
Mission
The mission statement is ‘everyone counts.’
Countdown achieves the mission statement in daily operations by offering attention towards
understanding the exact needs of the customers. The supermarket has developed decision making
systems that anticipate the specific needs of customers. All major decisions made at Countdown
arise from customer demands to ensure that customers get the expected satisfaction (Jiang,
2011). Furthermore, the management focusses on the improvement of employees through
teamwork and the provision of safe working conditions. Likewise, the management ensures the
improvement of the society both in financial and non-financial terms. Therefore, Countdown
plans different corporate social responsibility activities to improve the community and
environment.
Corporate structure
Countdown supermarket has developed a chain of leadership to steer the operations in the right
direction to top the retail industry. The top management position is occupied by the managing
director who is appointed directly from Woolworths Australia. The role of the managing director

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is to oversee the implementation of company strategies such as Customer 1st, business
transformation and spreading the Woolworths culture across the departments.
The general manager operations and logistics is second after managing director. The operations
and logistics manager leads the store and retail support team. The responsibility is to ensure that
the retail and stores team understand customer needs and stock the necessary products on the
shelves.
Countdown has a general merchandise manager who heads the produce department. The
manager is responsible for sourcing products, ensuring smooth operations and upholding high-
quality standards. The manager has a chain of command made up subordinate operations and
procurement staff.
Countdown has a corporate affairs, safety and stability department headed by a general quality,
safety and sustainability manager. The manager has the responsibility of setting up health and
safety standards in the supermarket to protect employees and customers. Additionally, the
manager is responsible for organizing corporate social responsibility activities to maintain a
positive image in the market.
Major business processes
Countdown supermarket has split operations into three core processes. The processes include
such as,
1. Sourcing of produce – the supermarket gets the best quality of products from the local
farmers (Apiletti, 2017). The supermarket has entered into supply contracts with the local
suppliers to ensure the maintenance of high-quality products. The supermarket assists the
Managing
Director
General
operations and
logistics manager
General
merchandise
manager
Head of
corporate affairs

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farmers to take care of products such as grocery and animals to result in the best quality
for the market (Bacardit, 2014). Countdown buys products straight from the farms and
stocks the shelves an activity that has resulted in high customer satisfaction.
2. Warehousing and storage- the supermarket has adopted the cross-docking approach to
prevent the storage of products in warehouses (Bacardit, 2014). However, the
supermarket engages in warehousing where staff maintains a safety stock amount to
ensure the smooth running before order delivery. The warehouse staff also engage in
value addition activities such as product packaging, sorting and branding before shelving.
3. Customer service – the supermarket prides in providing consumer products in the shelves
at affordable prices (Bacardit, 2014). Furthermore, the supermarket has managed to
provide fresh produce on the shelves for customers to access. Customers enjoy a wide
selection of products availed in the supermarket.
Business strategy
Countdown has adopted the market growth strategy with the aim of increasing sales and
revenues (Apiletti, 2017). The supermarket acknowledges the competition posed by other major
supermarkets in the country. The competitors try to win market share through price wars and
high-quality products and services. Therefore, Countdown supermarket responds by developing a
market growth strategy that specializes in offering fresh farm produce at affordable prices that
competitors fail to match. The strategy has resulted in the company becoming a leader in the
market by hurting competition by offering low prices and very high-quality products.
Relationship with external entities
The supermarket has managed to maintain healthily and friendly relationships with external
bodies (Choi, 2017). For example, the supermarket aims at protecting the environment through
the incorporation of energy-saving lights to minimize the rate of carbon emission. Countdown
Supermarket has managed to engage the society in training sessions that emphasize the
importance of environmental protection. The efforts saw the supermarket fetch the Green
Ribbon Award from the Australian government.
On the other hand, the supermarket maintains a friendly relationship with other players in the
industry. The supermarket has managed to introduce ethical and fair market practices that keep
competitors happy (Choi, 2017). Therefore, Countdown lacks corporate enemies who could
maliciously attack the supermarket’s positive image.

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Countdown homepage URL
https://www.Countdown.co.nz/
Part 2
2.1 IT infrastructure
Hardware platforms
Countdown has purchased efficient hardware to support information technology based
applications. The supermarket has installed super computers with adequate processing power and
storage for easy operations. The computers ensure smooth functioning of the information
systems by detecting problems and developing real-time solutions. The employees also use
portable devices such as phones, laptops and IPad to monitor operations.
Internet platform
Countdown supermarket has an E-commerce infrastructure that plays a huge role in customer
service (Dong, 2018). The E-commerce platform is made up of enterprise resource planning and
customer relationship management software. The two applications form an online management
system for the supermarket that assists in customer service and inventory management.
Additionally, the customer relationship and enterprise resource planning software form the basis
of the online shopping application availed to customers (Jiang, 2011). The online shopping
application is hosted at the supermarket’s headquarters by powerful computers equipped with
adequate storage and processing abilities.
Database management and storage
Countdown supermarket has allowed customers to register important information in the online
shopping application (Dong, 2018). The application has features that allow customers to enter
details such as payment information, location, name and workplace. Customers login into the
supermarket’s website and select the online shopping feature, which opens up a window that
displays products with the prices. The customers shop products by adding to a virtual cart and
sign out by paying online to confirm delivery. The supermarket staff uses the personal details
given by the customer to deliver the products. The online application has played a huge role in
increasing sales and revenues since the website avails all products needed by customers (Jiang,
2011).
Mobile digital platforms
Countdown has developed a shopping application to run on various devices (Horton, 2015). The
application serves customers using smartphones and laptops with the only requirement being an

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internet connection. Furthermore, the customers have the choice of downloading the application
from online shops such as Google Play and Apple store or browse online using search engines.
The application is customer friendly thus customers require minimal assistance to navigate while
shopping for products.
Enterprise software planning
On the other hand, Countdown has an enterprise resource planning (ERP) system that ensures
that inventory levels are at optimal levels (Huang, 2013). The ERP system allows smooth
operations at the supermarket by giving timely information about inventory levels and demand.
The system maintains high accuracy levels by using real-time information from the market. The
enterprise resource system establishes demand levels in the market and informs the inventory
department to take necessary actions to align products on the shelves with demand. The ERP
system runs automatically with the help of artificial intelligence to calculate demand and send
detailed reports to relevant parties. The ERP system has managed to interlink the supermarket to
the suppliers of various products sold at the supermarket (Jaewook, 2012). The system informs
the suppliers to deliver products once the inventory reaches the safety stock level. Consequently,
the supermarket has managed to avoid product shortages on the shelves. Therefore, the
infrastructure adopted a Countdown supermarket has managed to bring together various
components together with an ability to send messages over a network. Consequently, the
supermarket manages to keep customers, suppliers and other parties updated with necessary
information about operations.
2.2 Issues and challenges in managing IT infrastructure
Lack of powerful computing equipment
Countdown supermarket suffers from lack of adequate processing power to run the enterprise
resource planning and online sales software (Jaewook, 2012). The supermarket faces challenges
especially during peak hours when customers place multiple orders simultaneously. The problem
is rampant especially on the online shopping application since customers’ access at once in times
such as during festivities or during great discounts and offers. The available hardware of the host
computer lack power to execute the orders in time resulting in application downtime and
customers cannot access services (Huang, 2013). Therefore, the information technology manager
is on the constant lookout for powerful computers to host both the ERP and online shopping
applications.

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Problems of acquiring data
Countdown supermarket incurs the challenge due to the customers who install firewalls to
protect emails and other personal information (Jiang, 2011). Some of the firewalls erase
customer data from third party websites leaving no trace. Therefore, the supermarket suffers
from a similar challenge when customer firewalls delete customer information from shopping
applications. The delivery staff faces challenges trying to reach a customer for delivery purposes.
Lack of efficient data storage
Countdown supermarket faces the challenge of inadequate storage capacity to maintain useful
information such as customer details and inventory records (Jiang, 2011). The supermarket ends
up losing much information by deleting old data to create space for new information. The
supermarket has adopted cloud computing, which has currently become popular with institutions
that handle large amounts of data (Horton, 2015). However, despite the successful
implementation of cloud storage systems, the supermarket still faces challenges since most of the
applications lack compatibility with cloud back-up systems.
Poor network connections
Countdown sometimes suffers from poor network connectivity that hinders online activities
(Jaewook, 2012). The ERP and online sales systems involve constant sending of messages over
networks thus without a proper internet connection, the activities fail. The supermarket faces
challenges serving customers and communicating with external parties during times when the
internet connection is slow.
Computing management
Countdown faces the challenge of inadequate computing facilities to deal with the huge data
received from customers (Jiang, 2011). The customers keep sending orders on the online
shopping platforms, which results in an overload of order execution systems. Therefore, the
supermarket faces difficulties in the automatic assignment of customers to sales representatives
who ensure product delivery. Furthermore, online customer service systems result in the
exchange of excessive data over the network (Dong, 2018). Therefore, the systems end up
freezing, which translates to poor services among the customers.
2.3. Adoption of emergent technology
Countdown supermarket has made significant strides towards the adoption of new technology
(Countdown Marches on with Convenience for Connected Customers | GS1NZ, 2019). The
greatest achievement until now is the online shopping platform that customers have come to

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appreciate due to the luxury of ordering products and waiting for delivery. The customers also
pay for the goods online without fear of credit card records being used for unauthorized
withdrawals and purchases (Countdown Marches on with Convenience for Connected Customers
| GS1NZ, 2019). Additionally, the online shopping system has allowed the supermarket to avail
customers a 24/7 support system where customers get timely responses for questions asked.
On the other hand, the supermarket has integrated enterprise resource planning systems that
manage inventory (Technology in Supermarkets, 2019). The system automatically detects the
level of inventory available on the shelves and in the stores and makes necessary reports to
initiate the right actions. The ERP systems and the online shopping platform are the only
technological advancements made by Countdown supermarket.
Recommendations for new technology
Countdown supermarket could introduce artificial intelligence to revolutionize shopping
experience (Spath, 2013). The integration of artificial intelligence into shopping activities will
increase customer comfort while buying products. The artificial intelligence will introduce
various efficiencies such as robot deliveries to customer locations and shopping for customers at
the stores. The artificial intelligence will have the ability to collect customer information to
establish shopping patterns. Therefore, the artificial intelligence systems will use the information
to shop on the customer's behalf.
Countdown can introduce artificial intelligence to assist customers when shopping for groceries
since most customers have a predictable pattern (Ruan, 2017). Therefore, artificial intelligence
will easily monitor customer trends and other characteristics to aid in shopping on the customer's
behalf in the future. Furthermore, the artificial intelligence technology will reduce time spent
shopping and delivering products to customers due to the ability to detect customer needs early
before making orders.
2.4 Challenges of artificial intelligence
Provability
Countdown supermarket will experience challenges demonstrating and explaining to the
customers how artificial intelligence works (Merritt, 2018). The technology uses a complicated
mathematical formula that the supermarket will find hard to explain to the customers. Therefore,
the customers will be skeptical about the technology due to a lack of adequate information about
the mode of operations. The customers will have trouble understanding how artificial
intelligence makes decisions. Additionally, customers will lack clarity on the decisions made by

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artificial intelligence causing further reluctance in acceptance (Ruan, 2017). Therefore, the
supermarket should develop artificial intelligence systems that customers can understand without
a doubt.
Data privacy and security
The artificial intelligence uses data to learn customers and make decisions about shopping
activities and trends (Spath, 2013). Most of the data collected from customers of highly sensitive
and could cause a serious breach of privacy. Malicious persons could use the information for
unauthorized activities that could harm the customers. The lack of assurance about the privacy of
information will result in fewer customers using the technology to avoid a possible breach of
privacy.
Algorithm bias
Artificial intelligence technology is only as good or bad as the data trained on over a period of
time. Bad data often associates an organization with social vices and insensitivity such as racism,
gender and ethical bias (Sudhahar, 2015). For example, artificial intelligence use data such as
Google photos collected from a customer. The photos post a risk of misinterpretation when
cameras miss a mark on racial sensitivity. Additionally, artificial intelligence technology might
miss the exact location of a customer during delivery caused by a failure in GPS trackers and
satellite location signals. The customers and supermarket might end up incurring losses.
Scarcity of data
Despite the fact that Countdown supermarket has collected huge amounts of data years, artificial
intelligence will still lack appropriate data to use. The reason for the lack of data lies in that
artificial intelligence requires specific data to learn from (Xiang, 2016). The system will require
properly labeled data and supervised training. Additionally, artificial intelligence ingests
specifically formatted data that is compatible with the software. Currently, Countdown
supermarket has not collected such data, which will cause problems when training the artificial
systems.
Part 3
3.1 The definition of big data
Big data generally refers to the activity of collecting huge and complicated sets of information
(Merritt, 2018). The collected data sets present a difficulty to process using traditional database
management and processing tools. The data exists in various formats that include structured,

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unstructured and semi-structured. Formally, the data is described form 3Vs to 4Vs meaning
volume, variety and velocity (Ruan, 2017). Volume relates to the amount of data provided on a
daily basis for use. Velocity of data is how fast the data flows from the gathering stage to
analysis. Variety, on the other hand, refers to the types of data collected that includes the
structures of the information collected during a time period. The fourth V represents veracity,
which is described as the availability and accountability of the data collected. The predictions
into the future of big data show a constant growth in usage up to 25 billion. The statistics show
that big data is the next big step in the future of information technology.
The potential of big data
Internet of things for big data analytics
The current developments on the internet have restructured the interrelations on a global scale in
the art of commerce, culture and personal characteristics (Apiletti, 2017). Machines have
advanced to control a variety of gadgets via internet and the creation of internet of things
applications. Therefore, daily used gadgets have begun using the internet, a development that has
aroused the attention of researchers to find the most promising opportunities and challenges. The
developments have an impact on both economic and social trends with the promise of a future
where every gadget will connect to the internet (Bacardit, 2014). However, despite the promising
developments, the internet of things poses data challenges regarding the 4Vs (velocity, veracity,
volume and variety). Therefore, big data analytics has a great potential for solving the challenges
through computational intelligence. Therefore, the integration of big data analytics into the
internet of things will improve data management and discovery of knowledge on a large scale
basis.
Internet of things researchers realizes the fact that the acquisition of knowledge will pose great
difficulty in the future (Choi, 2017). Therefore, developing proper infrastructure to analyze data
dealt with in the internet of things is very important making big data analytics an important
aspect in the future of data and knowledge management.
Cloud computing
Big data analytics has great use in the current trend of cloud computing (Jaewook, 2012). Cloud
computing has allowed virtualization of software with the availability of a flexible number of
processors, storage space and a properly operating system. The integration of big data analytics

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to cloud computing functions will allow immediate access of data. Cloud computing holds huge
amounts of data that is required on demand by the users through configurable virtualization
techniques.
Researchers have identified various challenges associated with cloud computing regarding data.
Cloud data systems make money from users paying for resources and use for a specified activity
(Horton, 2015). Therefore, big data analytics will play a great role in processing data in real-time
to save customers money paid for service use. On the other hand, the customers will get better
knowledge since big data analytics have great power to filter information and avail only useful
information.
Uses of big data analytics in business
Decision making
Big data analytics is important in business decision making on a daily basis (Jiang, 2011). The
management of today businesses faces various situations that require detailed information and
little time to make decisions. The managers lack the luxury of time to read various reports or
research for information to get answers since the business world changes rapidly. Therefore,
businesses are using big data analytics to make decisions regarding various situations (Jaewook,
2012). Big data analytics systems have large volumes of detailed data collected from various
sources such as scanners, social media, website’s, credit cards and mobile phones. The data plays
a great role in managerial decision making since big data analytics has the potential to
summarize the information and provide useful reports.
Quality management and improvement
The quality improvement will mostly benefit manufacturing, health, telecommunication and
energy industries (Merritt, 2018). Big data will assist in increasing profitability, customer
satisfaction and cost reduction by boosting the quality of products offered to the market. A good
example is in the manufacturing processes where big data analytics ability to predict helps to
reduce performance variability by giving early and timely alerts to management. The action
plays a big part in reducing scraps and minimizing the time of moving products to the market.

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Business opportunities and benefits of big data
Predictive analytics consultancy
Big data analytics has opened up a great opportunity for individuals and companies to access and
interpret data for useful information (Jiang, 2011). However, not all companies have the
resources to introduce big data analytics due to various shortages such as lack of expertise and
resources to run the technology. Therefore, an opportunity arises in the market to provide
predictive analytics services to companies that would like to outsource from external experts.
Fashion trends analysis and forecast
Businesses dealing in the fashion industry have come to acknowledge the dynamic nature of the
market since customers rapidly change taste and preferences (Ruan, 2017). Therefore, an
opportunity arises to provide fashion trends analysis from the manipulation of data collected
from different customers. The ability to provide a robust solution that can enable manufacturers
and cloth retailers to understand changes and align with market trends will result in high profits.
Problems of big data analytics
Storage and analysis
In recent years, organizations have held an exponential amount of data relating to operations and
customer behavior (Spath, 2013). The data has been collected from mobile devices, websites and
social media platforms. The data was previously stored in physical storage equipment such as
hard drives and CDs until the development of cloud computing services, which charge for a
specified amount of storage. Therefore, companies have not yet come up with means of storing
data that have unlimited storage and does not result in expenses. Consequently, the huge amount
of data that accompanies the use of big data analytics poses a challenge to companies regarding
the storage of the information (Sudhahar, 2015). On the other hand, companies lack adequate
computing power to process huge amount of data collected in big data analytics.
Security of information
In big data analytics, huge data is collected and stored within an organization’s information
system (Singh, 2010). The data is correlated, analyzed and mined from various private sources of
customers. Various organizations have set up standards to protect customer information such as
installing firewalls and anti-viruses. The protection protocols protect information from malicious
individuals who could use the information for harmful activities (Wu, 2017). However, despite
the installation of various security protocols, the protection of information has become difficult

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with time since unauthorized persons keep developing advanced methods of accessing
information. Therefore, organizations still incur security challenges such as hacking and
destruction of stored information.
Future of big data
Server-less architecture
Big data analytics technology is moving towards the achievement of serverless technology that
will enable the hosting of applications by third parties (Xiang, 2016). The third party hosting will
eliminate the need for managing software and hardware by application developers. The
applications will exist in a broken format that users can use individually without having to access
other sites.
1. Server-Less technology will have the following benefits.
2. Ability to pay only for the application that a customer uses
3. Reduction in the time of implementing orders
4. Tolerance of mistakes and full-time availability
3.2 Big data strategy
Reason for investing in big data
Countdown supermarket should invest in big data for the following reasons,
1. To have adequate customer information
2. To make better market decisions
Big data will help in increasing customers’ information due to the ability to collect data from
various sources such as social media, websites and mobile phones. The increased information
will help in determining shopping trends such as the items bought most, time of shopping,
location of residence and occupation (Wu, 2017). The data will enable Countdown to profile
customers in a more accurate manner.
On the other hand, big data technology will assist in decision making due to the ability to collect
information regarding various aspects of the market (Sudhahar, 2015). Countdown supermarket
can use the information to understand customer demands and preferences. Additionally, with the
information, the supermarket can make informed decisions about how to respond to changes in
the market.

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Key areas of impact
Customer intelligence
Big data technology has great potential in increasing Countdown’s supermarket customer
intelligence. Big data collects data from various sources such as websites and social media
(Ruan, 2017). Therefore, Countdown will perform various activities such as customer profiling,
targeting and segmenting in a better manner. Consequently, Countdown supermarket will make
better marketing decisions that will result in a higher level of customer satisfaction.
Quality improvement
Big data technology has the ability to predict the future of operations by analyzing trends of data
collected (Ruan, 2017). Therefore, Countdown supermarket will manage to understand possible
errors that could happen in the future and put up measures to mitigate. Therefore, the
supermarket will maintain high-quality services at all times.
Risks to consider and mitigation
Big data technology carries an inherent risk of a malicious attack from unauthorized users. The
attacks could come from Sybil attackers and hackers (Spath, 2013). Unauthorized persons could
use the information for harmful and illegal activities. For example, a hacker could access
information regarding customer credit cards and proceed to withdraw money from bank
accounts. On the other hand, the attackers could delete important data from the big data storage
systems.
Mitigation
The use of encryption and authorization systems could play a huge role in protecting big data
(Merritt, 2018). The security procedures have the ability to lock out unauthorized persons from
accessing the stored data. For example, encryption stores the information in a format that only
authorized persons can decrypt. Authorized persons have passwords and codes to use while
decrypting the information. Therefore, unauthorized persons without security protocols lack a
means of accessing the data.
Supporting tools and skills needed
Tools
1. Computers
2. Storage hard drives
3. Cloud computing software

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4. Data analysis software
5. High processing power
6. Firewalls and anti-viruses
Skills
1. Data analysis
2. Data encryption
3. Blockchain technology
4. Artificial intelligence
Measurement of success
Increased customer information
Countdown should measure an increase in customer information such as shopping trends and
patterns. The information should come from many sources such as mobile phones, social media
and websites due to the implementation of big data technology (Singh, 2010). Furthermore,
Countdown supermarket should have constant reports about the changes in customer behavior
and shopping patterns arising from the implementation of big data technology.
Composition of the governing body
• Managing Director
• General operations and logistics manager
• General merchandise manager
• Head of corporate affairs
• Head of information technology
• Project manager
• Head of marketing
• Representative of employees
PART 4
4.1 Conclusion
The report discusses various aspects of Countdown supermarket information technology
infrastructure. Countdown supermarket has developed two information system applications to
serve customers and operate efficiently. The applications include,
1. Online sales

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2. Enterprise resource planning
The supermarket has adopted emerging technology in the form of the named applications.
However, with the dynamic changes in infrastructure, the supermarket should implement a
current technology such as artificial intelligence. The technology will revolutionize shopping and
customer experiences at the supermarket.
Furthermore, the report discusses aspects of big data technology such as uses, opportunities,
problems and future developments. Countdown supermarket should invest in big data technology
to improve the business in the following areas,
1. Customer intelligence
2. Quality improvement
However, Countdown supermarket should not ignore various challenges posed by big data
technology. The challenges include,
1. Storage and analysis problems
2. Security of information
Recommendation
The problems should not give a reason for failing to implement big data since solutions such as
encryption and authorization protocols exist to protect information. Therefore, Countdown
supermarket should invest in technology and enjoy the benefits of holding more customer
information. Furthermore, Countdown supermarket will have a better understanding of customer
tastes and preferences, which have shifted to the online platform. Most customers watch ads,
shop for products and pay for goods online. Therefore shifting to the digital world is the only
way to appeal to the new breed of customers.

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