Big Data_Retail Apparel_Dubai

Big Data zeroes on Apparel
Akanksha Chaudhary1
, Ankit Sinha2
, Arpan Chandra3
, Akshay Maheshwari4
, Savidh Soni5
Keywords: Big data, business Intelligence, Hadoop, Analytics
Abstract: The aim of this report is to provide insights on how big data can be used to analyze the smallest consumer behavior
as well as the largest global trends in retail apparel. Big data is identified as one of the major technology trends of 2014. It
encompasses huge volumes of unstructured, structured and semi-structured data running into exa-bytes that cannot be
analyzed using traditional or conventional data analytics systems or platforms. The advent of new systems such as Hadoop
and SQL has now made it possible to interpret the enormous amount of data. Big data analytics would help retail businesses to
predict shopper behavior and personalize consumer experiences by gathering as much information about the behavior,
shopping history, and interests of consumers, thus enabling retailers to implement a dynamic pricing, personalized
recommendations, shopper-specific discounts, and more.
Introduction
The retail apparel industry comprises of clothing, accessories
and footwear. It is currently a multibillion-dollar industry.
The retail apparel portion of the overall market is expected to
generate $3180 billion in 2015 with a yearly growth rate in
excess of 4%. China, UAE and Chile are the top three top
three developing countries in terms of market attractiveness,
retail development and country risk for their clothing retail
industries, according to the AT Kearney 2013 Retail Apparel
Index. Dubai's economy has been progressing very rapidly
and this has made difficult for the retailers to adapt to the
changing needs and preferences of the consumers. Retail
map in UAE has grown from the traditional culture of local
markets to that of more organized and sophisticated modern
culture of malls with international retail chains and brands
trying to establish themselves. The retail industry makes up a
third of Dubai's economy according to the Oxford Business
Group and it has identified Dubai for major expansion.
Fig.1: Predicted Global Apparel Sales till 2018
Interestingly, the global apparel industry has experienced
dramatic changes in demand over the last few years due to
the economic downturn post 2009. Even though it was not
impacted as adversely as compared to other sectors of the
economy, it wasn’t spared either.
As the economy recovery is continuing to gain strength,
apparel industry is gradually feeling the effects of improving
business. Retailers and brand owners have passed the
turbulent times with resilience but not without taking some
stringent measures and in the same process some firms have
significantly fallen out of the business. The industry is still
facing some challenges.
Over the years price reductions to increase demand, boost the
buying behavior of the consumers and lure them has affected
the industry in the form of lower prices and less profit
margins. Apparel retail out of stock rates average 10-12% as
retailers try to ensure adequate shelf availability while at the
same time limit the amount of inventory they carry to avoid
costly markdowns on unsold merchandise.
To overcome these challenges apparel industry is planning to
find ways to stretch the boundaries of its creativity and
imagination to find new ways to increase selling
opportunities, reduce operating costs, achieve competitive
advantage and improve the bottom line.
Apparel retailers and brand-owners are stepping up their
efforts to marry improvements in business processes with
innovative technology that touches every step in their
workflows, often collaborating to create synergistic, holistic
solutions from the manufacturing source through distribution
and all the way to the retail store’s back room, sales floor
and point-of-sale. Industry is exploring technology-based
solutions to spot the global trends, changing consumer
behavior and growing awareness of industry practices to
provide invaluable shopping experience to the customers.
Many companies have started outlining the Key performing
indicators, a.k.a. KPI(s) to translate strategy execution into
quantifiable terms. It allows an organization to see where it's
doing well and where it requires improvements and/or course
adjustments.

Basically KPIs are metrics that are: Outcome-oriented,
Target-based and can be Rated or graded. Based on this,
some of the significant performance measures are: Customer
Analytics, which understands customer requirements and
deals with ever-changing market conditions The pointers to
look out for are- Average number of items per transaction,
Average shopping time and Visit to buy ratio.
Fig.2: Top three Best-in-class retailer BI strategies
The Financial Analytics deals with tracking trends in product
demand and opportunities in sales. Marketing analytics can
help us track effect of campaigns in sales and help us target
customers and plan for promotions. The pointers to look out
for are- Total Sales, Gross Profit Margin, Price premium and
Actual expenses.
The Store Analytics monitors store operations vital to
measure management efficiency and how campaigns
are working regionally. The pointers here to look out for are-
Sales per hour, Number of transactions per hour, Percent (%)
of returning customers and Inventory Turnover.
Apart from these, there are many other behavioral aspects,
which this industry is targeting on. Some of them are:
Cross-Selling Techniques
Cross selling means that a company has the access to
customer data that deals with demographics, preferences,
past purchases, locations etc. This helps the retailer to
analyze the market trends and try and sell a different type of
a product to an existing customer.
A basic example of cross selling would be in the case of a
retailer who tries to sell a new design of apparel to an
existing customer. This is possible only if the retailer has
adequate information about the customer. Amazon.com
deploys collaborative filtering to produce “you might also
want” prompts for all product bought or visited. At one
point, Amazon stated that 30 percent of sales were through
its recommendation engine.
Emergence of Omni Channel Retailing
Retailers need to be creative enough to be able to connect
with the consumers using various means of communication.
This has compelled retailers to approach the consumers and
enhance their shopping experience through various channels
such as TV, internet, radio, brick & mortar, emails, etc. It
also enables the retailers to promote their products through
various channels in order to boost their sales. UK fashion
retailer Oasis is doing a very good job in Omni channel
retailing. The merchant gives customers the flexibility to
browse inside the store, then purchase online and vice versa.
Shoppers can have their products shipped, or they can choose
to pick it up.
Location-based Marketing
Location based marketing has emerged in the recent past, all
credit to the availability of modern technology such as cell
phones and GPS systems. The retailers are now able to
connect with the target customer base with the help of
mobile technology. Retailers are able to target the customer
base based on the area of operations.
Brick and Mortar Stores
With the advent and popularity of online shopping portals it
has become very crucial for the retailers following the brick
and mortar model to be innovative in order o cope up with
the growing competition. One way of overcoming such a
stiff competition is by way of analyzing the available data
related to the customer history. Big data may be useful and
may come handy. For example Burberry once invited
customers to its store to live-stream the London Fashion
week.
Behavior analysis
Customer preferences and attitudes towards the designs play
an important role in the growth of a retailer in the apparel
sector. It is vital for the retailer to observe the behavior of the
customer who has walked into the store in order to constantly
update the stock as per the changing preferences. Even
though retailers are now able to capture the behavior of
customers who enter into the store, it is very important to be
able to interpret it correctly. Tools such as big data can assist
in analyzing the behavior of the customers.
Loyalty Programs
Retailers can come up with creative loyalty programs if they
are able to analyze the buying trends of the customer. This
would enable them to target the growing spending power of
the customer by retaining the existing customers by way of
loyalty programs. But this is possible only if the retailers are
able to analyze the available data, which would then help
them to come up with the most optimum plan.
For example office depot started implementing a program
that gives customers rewards based on their frequently
bought items, shopping behavior and the amount information
that they shared with the brand.

Figure 3: Design to reduce marketing cost
Customer Segmentation
Retailers need to segment the customers based on various
factors such as location, age, incomes, preferences, etc. This
is possible only by way of using sophisticated tools such as
big data which is able to analyze large amounts of data and
provide a recommendation. This would then enable the
retailers to price and position their products accordingly
Assortment optimization
It is important for any retailer to position one’s product in
such a way that it is able to attract the interest of the
consumer. The decision about the same depends on factors
such as preferences, age, incomes, etc. This would enable the
retailer to place the products on the basis of local
demographics and buyer perception.
Price optimization
Retailers can benefit from the availability of data and its use
by way of analysis which would help them to optimize their
price. Analysis of data collected from various sources and
locations would provide the company access to the data
dealing with different tastes and preferences of consumers
across a large geographical area. This could help the
company to price its products in a more optimal manner
depending on such factors. This process of price
optimization would ultimately lead to profit maximization.
Space optimization
Brick-and-mortar retailers can benefit by way of utilizing
their space in the most optimum way and also ensuring that
they do not compromise with regards to the display of the
store which would attract the customers. Data analysis can
help to understand customer behavior which can then be
analyzed to place a product accordingly in a store and
optimize the space available.
For example, eBay has
conducted manifold experiments on different aspects of its
Web site to find optimal layout.
The global apparel retail industry generated revenues totaling
to $1,323.6bn in 2013, with a compound annual growth rate
(CAGR) of 4.1% between 2009 and 2013.The womenswear
segment was the best performing segment in 2013, with total
revenues of $660.4bn, equivalent to 49.9% of the industry's
overall value. The industry is expected to grow at a CAGR of
5.1% from 2013-2018 and the market is expected to touch
revenues totaling to $1,695.6bn by the end of 2018.
Source: MarketLine – Research Store
It is quite evident from the above that the global retail sector
is a very promising one considering the fact that it is
expected to grow at a stable pace over the years. Although
this indicates plenty of opportunities in the coming years
across the globe, almost all the retail companies globally are
also facing certain challenges that need to be addressed in
order to ensure that the dream run to 2018 is not hindered
due to bottlenecks of inefficiencies or lack of resources.
Some of the key challenges faced by retailers around the
globe are:
Competitive pricing: The global market has become very
competitive with the advent of multiple brands catering to a
particular segment of people. Consumers now have a large
variety of products to select from and are spoilt for choices.
Also the emerging markets are extremely price sensitive and
the demand from such regions is expected to grow rapidly in
the coming years. This forces the retailers to remain
competitive as compared to their peers in order to survive in
the market
1. Procurement and logistics: At the international level it is
essential to be able to provide the right product at the right
time to the right consumer. In order to be able to do so,
retailers need to have a fool proof procurement and logistics
process in place that ensures that the products reach the
consumers when demanded.
2. Quality and reliability: Quality has now gained global
importance and consumers place quality as one of the
prerequisites of buying a product. Retailers need to ensure
that the quality is maintained and improvised with time
3. Consumer preferences: Consumer preferences are dynamic
and are continuously evolving. Hence it is equally important
for retailers to be innovative so that they can provide better
products to the consumers. Products also need to evolve with
time in order to cater to the changing preferences of the
consumers
4. E-commerce: The brick-and-mortar retailers are facing stiff
competition from the e-commerce vendors. Apparel retailers
now need to come up with innovative ideas to promote their
products in order to keep up with the stiff competition of the
e-commerce industry
5. Large Data: Retailers collect and storage large amounts of
data on a daily basis but are unaware about the usefulness
and the interpretation of such data. Techniques that help in
analyzing such data can help in serving consumer
preferences better in the coming years.

Adapt to Change…Now!!
Here is what some of the industry leaders feel about the need
of greater customer intimacy by overcoming the above
challenges and tapping new opportunities.
“The idea of customer-centric marketing cuts across the
major technology trends for 2014. It’s really about using
technology to return to the early days of retail — when every
shopkeeper knew each and every one of his or her customers
as individuals — but at scale."
Daniel Druker - Chief Marketing Officer - MyBuys
@DDruker
“The retailers that are able to tap into integrated customer
data repositories, mine it for consumer insights and then
execute promotional campaigns that are truly relevant to the
consumer will be the big winners in 2014."
Lori Mitchell-Keller - Head of Global Retail Industry - SAP
@LORIMITCHELLKEL
Retailers need an innovative process/tool that can help them
to turnaround their current business processes and help them
become more efficient and customer focused. Lot of data is
collected by companies on a daily basis which is not used
effectively. Companies need to analyze trends using the data
collected and develop strategies to perform better. Retailers
rely on the data and strategies implemented in the past with
little changes assuming that the strategy will remain
foolproof even in the next year. But it is important to
understand that the world is dynamic and is changing
rapidly. The retail sector also undergoes changes on a
continuous basis with regards to preferences, prices, designs,
etc. Advertisements and promotions of a retailer are linked to
the strategy adopted.
However, if the strategy is not modified as per the changing
environment, there is not much chance that the company
would be able to perform better. Hence in order to ensure
that the market share is maintained at current levels or
increased, development of innovative strategies that are in
line with the changing preferences of the consumer is the
need of the hour. Customer is the king and with the changing
dynamics between the consumer and the retailer, the retailer
hardly has any influence over the consumer’s preferences.
Hence the retailer has to ensure that innovation takes place
on a regular basis in order to keep up with the changing
consumer preferences.
Implementation of an innovative technology that can assist
retailers to analyze the trends in the changing consumer
preferences has done wonders for an organization in the
retail sector. It has enabled them to exploit the current
markets in which they are operating and also open doors to
venture into new markets. It will also ensure that retailers
streamline their operations with regards to accurate pricing,
optimizing costs, removing obstacles in operations, most
optimum stocking (including the most preferred products
depending on factors such as price, design, location and time
of the year). It has become even more important for the
brick-and-mortar retailers to keep innovating and
streamlining operations considering the stiff competition
from the e-commerce companies. Such retailers are now
looking at using modern techniques/tools to analyze the
stored information and analyze trends that would attract
consumers.
Better data analysis can contribute in a positive way in terms
of higher sales, better KPIs, reduced costs, optimized store
spaces, streamlined processes and logistics, best promotion
strategies and of course higher foot falls i.e. customers.
Companies like Marks and Spencer’s was established in
1884, and it aims to be the market leader in retail apparel.
M&S launched one of the best innovations in technology, the
virtual rail. The virtual rail gives the opportunity to the
customers to browse and view their dresses on a 3 X 46”
touch screen, which is an imitation of the real clothing. This
is a 9 panel video wall, which uses digital signage and
displays a full catalogue. The company emphasizes that the
technology is a great success it is has been launched in the
Internet savvy countries.
Puma is one of the first companies to incorporate tablets
inside their stores. They provide their customers
Personalized shoe designing experience. This technology
emerged in 2010. Puma gave their customer an option to
create their own sneakers and give an order online or in the
store. They were given the option for fabrics, materials and
design on the I-Pad. The customers can design sneakers , the
way they want it to be. This concept was named as ‘Creative
factory’.
This concept is a great success and Puma still uses it as it is
very popular. Competitors like Nike and Adidas have also
imitated the concept.
Also, pushy sales are no more a trend in the Retail industry.
The Retail apparel industry has realized that pushing
customers for selling their products is the wrong strategy.
The companies have changed the trend and have started
investing in the relationship marketing. Relationship
marketing is to change the role of the store associates from
selling products to advising, building relationships and
solving problems. The associates will provide tailored
advices according to the taste and choice of the customers.
Retailers have started investing heavily in training their
employees so that they build relationships and long lasting
customers.
Hackett is luxury apparel retail chain from United Kingdom
that now has stores almost all over the world, which has
invested in relationship marketing. They have trained their
store associates to build relations with customers and advise
them which helps Hackett build a better customer base.
Hackett has achieved a huge increase in the number of
repeated and loyal customers.

Although companies have started to contemplate on the fact
that better innovative techniques can help them to perform
better in business, it is still in the initial phases. Very few
sectors (including retail) have started to use such techniques
in their day to day operations. The use of such
techniques/tools can span across sectors enabling businesses
to benefit from its advantages. The issue faced by
organizations today is not the quantity of data but its
interpretation. At times it becomes extremely difficult for the
management to use and analyze the data due to its
complexity as they are unable to relate to the data available.
The issue faced in most cases is not due to the size of the
data but its complexity to be understood. This raises doubts
over the long term sustainability of big data. However, it
must be noted that in the years to come data analytics would
be more complex and it is important that analysis techniques
are able to assist companies to analyze these large chunks of
data in a more meaningful manner with the help of better
techniques of analyzing and interpreting data.
Big Data to the Rescue
The model above emphasizes on the fact that with the advent
of modern technology and growing competition amongst
retailers for maximizing their share in the market, it is
important to maximize the use of various channels of
communication with the consumers (also known as Omni
channel retailing) and also optimize the various resources
available. Big data is an analytical tool that can analyze the
dynamic data available and provide required solutions for
implementation. Optimization of resources along with
ensuring to connect with the consumer through various
means in order to cater to their growing needs and
preferences would ultimately lead to success.
Data Driven analysis are needed because businesses have
realized that in order to predict shopper behavior and provide
truly personalized experiences, they would need to gather as
much information about the behavior, history, and
whereabouts of consumers. It helps to collect and analyze
vast trenches of data relating to personal lives to highly
sensitive information at work and is able to capture and
provide the output with regards to the trends of the
consumer. This analysis enables retailers to implement
dynamic pricing, personalized recommendations, shopper-
specific discounts, and more.
Data management has now evolved to be a very crucial
consideration for many organizations across the globe since
the size of data that companies generate or/and source has
increased by leaps and bounds over the years. It is very
crucial to analyze such data and evaluate the relevance of
such data to an organization. Many companies have realized
the same and have started using data driven analysis to
understand how they can transform their businesses and
grow. It might help in - improving effectiveness of existing
applications, build new applications if required, develop
customer database to serve the customer better and increased
loyalty, sales and growth.
All these factors would help to retain existing customers and
target new segments and markets thereby leading to a boost
in the revenues of a company. Data analysis would in this
way help an organization to grow in terms of increased
revenues and customer base and will assist an employee to
achieve his/her targets in the organization thereby paving a
road for growth.
Big data is changing the way companies are doing business.
This is because it has enabled the businesses to analyze the
data collected and develop strategies relating to day to day
operations of the company. Big data has assisted companies
not only with regards to their operations but it also extends to
activities such as mergers, consolidation, acquisitions, etc.
which requires companies to analyze large amount of data
before they come to a final conclusion. Big data provides
companies the added competitive advantage which is not
accessible to companies that are not using big data. With the
complex nature of business and considering the fact that our
environment is a dynamic one, data driven decision making
plays a very vital role in assisting managers to make sound
decisions as they are able to rely on the data that can be
supported by analysis and logical reasoning.
To take any decision whether related to office or personal
life, one needs data. This high volume and high-variety of
data, when processed, allow us to take decisions better by
getting a clearer picture and sometimes getting a different
picture of problem.
“Big data is high-volume, high-velocity and high-variety
information assets that demand cost-effective, innovative
forms of information processing for enhanced insight and
decision making.” [www.Gartner.com]. Today, the data is
generated from every sphere of world.

“Big data is being generated by everything around us at all
times. Every digital process and social media exchange
produces it. Systems, sensors and mobile devices transmit it.
Big data is arriving from multiple sources at an alarming
velocity, volume and variety. To extract meaningful value
from big data, you need optimal processing power, analytics
capabilities and skills.” [www.ibm.com].
This large chunk of data when transformed into information
will serve for the betterment of society and mankind. “The
ability of society to harness information in novel ways to
produce useful insights or goods and services of significant
value” and “…things one can do at a large scale that cannot
be done at a smaller one, to extract new insights or create
new forms of value.” [Book: Big Data: A Revolution that
Will Transform How We Live, Work, and Think].
In short, “Big data is a popular term used to describe the
exponential growth and availability of data, both structured
and unstructured. And big data may be as important to
business – and society – as the Internet has become. Why?
More data may lead to more accurate
analyses.”[www.SAS.com]
The five V’s that define Big Data are –
Volume- Tremendous amount of data is generated everyday
whether it’s the internal data such as customer’s transactions
or inventories data or external data such as whether data or
traffic data.
Velocity –The speed at which the data is gathering is
tremendous. The sole reason of high-speed data generation is
the digitalization of society.
Variety- The complexity between the data, which is raw,
unordered and can’t be processed without analysis adds a
new dimension to define big data. The variety attribute is
contributed with of large and diverge source of data
generation.
Veracity - Big Data is messy but trustworthy. The accuracy
and quality of data pose a big challenge as the amount of
data is very large.
Value – The last but not the least V is Value. If the large
amount of data available or stored is not able to provide any
meaningful information then it is useless. So the Value is the
most important V of all the five V’s of big data.
To tame the mishmash of Big data, various tools in the
industry have been developed such as:
Talend – It is a global Big Data integration platform. The
latest version of Talend 5.6 promises of creating new
benchmarks of big data profiling and productivity and will
broaden the spectrum of Internet of Things (IoT) devices
connectivity. The software uses Hadoop to boost
productivity and connectivity across the board.
Another is Splice Machine – Its a real time SQL-on-Hadoop
database. It is one of the powerful software that offers ability
to process real-time-updates.
Another offering is Google Charts- it is the free tool that
offers a wide variety for visualizing data, which is received
from the website. The advantage of Google charts is the
customization of page to provide a website look. The charts
can be implemented by simply embedding a JavaScript in
website. The ever increasing river of data needs to be stored
so that data can be reused for a greater amount of time. The
latest big data storage technologies are:
Optical Storage: The latest optical storage that is used by
enterprise widely is M-disc technology aka Millennial Disc.
The Hitachi Digital Preservation Platform (HDPP) currently
uses this technology.
GridBank: Gridbank won the Big data storage product of the
year for two years consecutively (2014 and 2013). The
product provide highly scalable and data management
solutions.
TCS Active Archive™: It combines the strong capabilities
of product development and process expertise of TCS in big
data. The EMC analytics platform and infrastructure of EMC
is use in building the software.
Every coin has two sides. The bright side of having too much
data is to extract information, which is more relevant in
making decision making while the negative side of too much
data results in stolen information or compromised networks.
As it seems that Big Data has created many security issues, it
also seems as Big Data analytics has provided the solution.
The big data security analytic tools can be used to accelerate
the detection of incident and reduce the number of false
positives.
Big data Model consists of five pillars and works on
principle of management controls and business values. The
first and basic pillar of model is Data Visualization and
Analysis. The large quantity of data is processed and turned
into information using analysis and visualization. The next
pillar of model is storage optimization and security. The
large data is optimized for storage using classification to
save costs associated with storage. The security of large data
can be beefed up using real time analysis of data.
The third pillar of model is Reduce Cost and Complexity of
E-Discovery. E-discovery is a way of reducing the cost of
action. In an effort to reduce the gap of ever increasing data
and cost, software models are relying heavily on Electronic
Discovery Reference Model.

The fourth pillar of model is Policy based Information
Governance. Gartner defines information governance as “the
specification of decision rights and an accountability
framework to encourage desirable behavior in the valuation,
creation, storage, use, archival, and deletion of information.
The last pillar of model is Intelligent data-driven Decision.
The data driven intelligent decisions help managers to make
timely and effective decisions.
Challenges Of Big Data For Retail Apparel In
UAE
Local Retail Apparel companies are having difficulty in
identifying the right data and determining how to best use it.
Building data-related business cases often means innovative
thinking and looking for revenue models that are very
different from the traditional business. These companies are
also struggling to find the right talent capable of working
both with new technologies and interpreting the data to find
meaningful business insights. Data access and connectivity is
also an obstacle. A majority of data points are not yet
connected today, and companies often do not have the right
platforms to aggregate and manage the data across the
enterprise. The technology landscape in the data world is
evolving extremely fast. Leveraging data means working
with a strong and innovative technology partner that can help
create the right IT architecture that can adapt to changes in
the landscape in an efficient manner.
Leveraging big data often means working across functions
like IT, engineering, finance and procurement, and the
ownership of data is fragmented across the organization. To
address these organizational challenges means finding new
ways of collaborating across functions and businesses.
Finally, security concerns about data protection are a major
obstacle preventing companies from taking full advantage of
their data.
Apart from all the above factors, 80% of Dubai’s population
consists of Foreigners:
• 42.3% -Indians
• 17% -Emirati
• 13.3% -Pakistani
• 7.5% -Bangladeshi
• 9.1% -Arab
• 10.8% -Others
Hence, it becomes extremely difficult to cater to the taste of
such a diverse population.
Although Dubai has been called the "shopping capital of the
Middle East” the trend actually started in early 2013 and
since then has started picking up slowly. Although capturing
the cosmopolitan market later than the west, it still does not
have enough competent data to predict and gain advantage
with big data sophisticated tools.
Methodology Adopted
To study the big data usage a survey conducted within 52 big
data users in various industries across the globe.
Respondents ranged from high level management to various
task oriented people. The trend thus obtained when studied to
understand conclusions for big data’s usage. The challenges
and opportunities with identifying gaps. It is observed that
Middle East has some gaps that can be covered by reading
the trends and opportunities in various regions.
Two types of users were identified who use big-data to
leverage on the basis of the way they collect data. A majority
of users that have been using data analysis for much more
than 3 years now use old documents etc. as their source of
data. Due to lack of knowledge and security concerns
regarding data they have not been leveraging on it as it was
expected. Other users who have recently been using data for
analysis, use unconventional sources such as social media
and online data to collect information. These users are aware
of the opportunities and capabilities of big data and are using
it intensively. Also, these users are outsourcing data for
processing and are leveraging on it with useful information
collected.
From the data collected, it was inferred that the high-level
management are aware of the opportunities and possibilities
of big data. But it was observed that the mid and low level
users are still unsure of the same. Approximately 30% of the
users have been using big-data for more than 3 years. It is
felt amongst users from around the globe that major
challenges in usage of big data are lack of knowledge and
awareness of its capabilities followed by poor quality of data
present.
More than 62% of the users feel that security is also one of
the issues in sharing data with third party vendors for
processing. High management users feels that cost is a huge
constraint due to which they support data analytics in house
rather than outsourcing. The lower management users feel
that security and company policies prevent outsourcing and
processing of data using third parties. In retail only 50%
agree that data analysis create importance for the retail
industry and provides several opportunities.
Compared to other industries the share is very low. Data
used in retail is collected from enterprise applications only.

The major challenge in usage of big data in retail is lack of
knowledge.
In Dubai only 80.4% users are aware of the opportunities of
data analytics in various fields, this percentage is 98% in the
northern region including the USA. Middle-east has been
leveraged from data analytic in the last 1-2 years whereas
others regions have been using it for past many years now.
Most businesses including retail are in favor of outsourcing
data analytics part which is similar in Middle East with
some, others still feel that there are security concerns in
outsourcing data processing
Challenges related to Data Analytics
Challenges faced by organizations in using Big Data
Obstacles to outsourcing for Data processing
Organizations interested in data Outsourcing to third party
Outsourcing related to specific sectors

Conclusion:
The above survey reflects that big data is slowly becoming as
the next big trend in retail apparel and retailers are also
realizing its importance to tap the opportunities. Also, as the
experts in Retails industry say, Customer is the pivot for the
retail apparel industry. All the activities that take place in the
industry are performed keeping the customer in the mind.
Data is not for the customer, the customer is the data in the
case of this industry.
Middle east is an emerging and immature market. The
growth rate of the retail apparel industry is very high. The
CAGR of this industry is 22% to 25% in the previous years.
The barriers of entry in this region are low which encourages
apparel brands to enter this region.
Challenges faced by the retail apparel Industry in the Middle
East show that there is no sharing on the market research
information in this region and is done individually by
companies. We cannot find the down trending and up
trending fashion as there are no agreements for sharing
unlike US which forms a barrier to explore the untapped
market.
Big Data does not exist holistically in this region as it is still
a immature market. Only a few companies are there which
are researching and collecting data. It will take some time for
the companies in this region to attain that mindset and
maturity so as to adopt this technology.
According to Andrew Rippon, Big data Expert, "The big data
has been potentially exploited by the Online Retail Apparel
Stores in Middle East such as Amazon and Souq to analyze
the consumer preferences and purchasing pattern. The major
problem the outlet retail stores in this region is facing is the
adoption of correct tools to analyze the huge volume of
data. The other reasons for region being reluctant on readily
adoption of Big Data are the closed governance structure and
strict privacy issues."
The Landmark group has utilized big data by introducing
Loyalty program called “Shukran”. This has helped them to
analyze sales and trends. It has also increased their customer
base and loyalty. Great opportunities exist for big data in
Dubai especially due to expo 2020 and the large chunk of
data the country currently has. Due to collaboration between
different fields like open source, big data, machine
intelligence has led to the expansion of the industry.
Enlisted below are the strategies that companies can adopt to
shrink the gaps that exist in Middle East and transform using
big data to big business.
First, Companies should identify the data sources that
currently exist, and how are they utilizing it.
Second, Which is the type of data source and analytics model
that will help them to find a solution to their existing
business issues and concerns. For e.g. if I want to understand
my loyal customers I need to find out which is the big data
type that will match my business problem and
Lastly formulate strategies, which helps to minimize the
regret of loosing new customers.
References:
MarketLine – Research Store
[1] R. Caves, Multinational Enterprise and Economic Analysis,
Cambridge University Press, Cambridge, 1982.
[2] M. Clerc, “The Swarm and the Queen: Towards a
Deterministic and Adaptive Particle Swarm Optimization,”
In Proceedings of the IEEE Congress on Evolutionary
Computation (CEC), pp. 1951-1957, 1999.
[3] H.H. Crokell, “Specialization and International
Competitiveness,” in Managing the Multinational
Subsidiary, H. Etemad and L. S, Sulude (eds.), Croom-Helm,
London, 1986.
[4] K. Deb, S. Agrawal, A. Pratab, T. Meyarivan,“A Fast Elitist
Non-dominated Sorting Genetic Algorithms for
Multiobjective Optimization: NSGA II,” KanGAL report
200001, Indian Institute of Technology, Kanpur, India, 2000.
[5] J. Geralds, "Sega EndsProduction of Dreamcast,"
vnunet.com, para. 2, Jan. 31, 2001. [Online].

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