M&S: Leveraging Big Data for Enhanced Decision Support & BI

This report provides an analysis of how Marks & Spencer (M&S) utilizes Big Data for decision-making and business intelligence. It begins by introducing the concept of Big Data and its relevance to modern organizations, particularly M&S, a multi-channel retailer with a vast network of suppliers and stores. The report outlines a Big Data strategy for M&S, including steps for identifying data sources, aligning with business goals, and integrating Big Data tools with existing systems. It also discusses the alignment of business goals with Business Intelligence (BI) and Big Data concepts, highlighting advantages such as predictive analysis, improved customer engagement, and cost savings. The technology stack, including the Cloudera platform and Hadoop ecosystem, is examined, along with the role of data analytics and NoSQL databases. Finally, the report touches on the importance of social media in decision-making and includes a five-force analysis and value chain analysis to provide a comprehensive overview of M&S's Big Data implementation.

Big Data & Decision-Making: Marks & Spencer
Executive Summary
Marks & Spencer is an organization that was found in the year 1884. The company was started
in a single market stall and has now grown to an international brand as a multi-channel retailer.
Currently, there are over 85,000 employees working with M&S and it has around 850 stores in
UK and 480 international stores in 54 locations across the globe. It is of utmost importance to
make sure that the information sets are adequately stored, organized, and maintained in the
organization. Big Data is a concept that emerged with the increasing need of data storage,
management, and organization. Big Data refers to the application of technology for automated
analysis, storage, and handling of the data sets. There are several Big Data tools that have been
designed which are being used in the enterprises for data storage and management. The report
analyzes the role and relevance of Big Data and its associated concepts for M&S.
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Big Data & Decision-Making: Marks & Spencer
Table of Contents
Introduction...........................................................................................................................4
Big Data Use Case: Marks & Spencer...................................................................................4
Big Data: Strategy and Steps............................................................................................................4
Alignment of Business Goals and Objectives: BI and Big Data.............................................6
Advantages........................................................................................................................................8
Technology Stack...................................................................................................................9
Cloudera Platform & Hadoop Ecosystem........................................................................................9
M&S Technology Stack...................................................................................................................10
Data Analytics along with MDM: Support to DS and BI.....................................................11
Support & List of NoSQL Databases for M&S..............................................................................12
Social Media and it role in Decision Making........................................................................12
Value Creation Process........................................................................................................13
Five Force Analysis.........................................................................................................................13
Value Chain Analysis......................................................................................................................13
Conclusion............................................................................................................................14
References............................................................................................................................15
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Big Data & Decision-Making: Marks & Spencer
Introduction
The business organizations in the current times make use of massive sets of data. Information
associated with an organization is its most significant asset and it is necessary that adequate
management and organization of the information sets is carried out. There are different projects
that an organization works upon simultaneously. Each of these projects has their respective
information sets that need to be managed. Apart from these, employee details, financial
information, sales data, customer information, business partner details, market information, etc.
are some of the information sets associated with an organization.
It is of utmost importance to make sure that the information sets are adequately stored,
organized, and maintained in the organization. Big Data is a concept that emerged with the
increasing need of data storage, management, and organization. Big Data refers to the application
of technology for automated analysis, storage, and handling of the data sets. There are several
Big Data tools that have been designed which are being used in the enterprises for data storage
and management (Venturebeat, 2016).
Big Data tools are being integrated and used with the decision-making & decision support
systems along with the data analytics tools under Business Intelligence. (Google, 2016).
Big Data Use Case: Marks & Spencer
Marks & Spencer is an organization that was found in the year 1884. The company was started
in a single market stall and has now grown to an international brand as a multi-channel retailer.
Currently, there are over 85,000 employees working with M&S and it has around 850 stores in
UK and 480 international stores in 54 locations across the globe. The supplier network of the
organization is spread to over 3,000 suppliers globally and the company sells stylish clothes and
home products to the customers. It also deals in the outstanding quality food (Qubole, 2016).
Big Data: Strategy and Steps
The strategy of M&S is to increase the top-line sale of the company. The business strategy needs
to be aligned with the business initiatives as:
 Enhancement in the percentage of customer loyalty card.
 Enhanced customer engagement
 Promotion of seasonal clothes with discount
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Big Data & Decision-Making: Marks & Spencer
The Big Data strategy and the associated steps will fall in line with the company strategy and
business initiatives.
Big Data Strategy
Step 1: M&S has a supplier network of over 3,000 suppliers. There are a total of close to 1,300
stores of the organization globally. As a result, there are abundant sources of the data sets that
are associated including the social media channels, external, and internal sources. In the first
step, these sources shall be identified and listed. These data sources will include:
 Customer purchase patterns
 Transactional data
 Social media channels and networks
 Customer and supplier contact details and demographic information
 Site Search
 Data from the mobile application
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Big Data & Decision-Making: Marks & Spencer
Step 2: The business strategy is to increase the top-line company sales and the business processes
that will support the strategy will include the expansion of customer base with maintenance and
enhancement in the quality of the products. Big Data analytics will be applied for identification.
Step 3: Big Data will be applied in the process of multi-channel marketing and sales for M&S. it
will provide the capability to achieve the business strategy on the basis of the customer
preferences and choices (Schmarzo, 2013).
Step 4: The critical success factors that are associated with M&S include understanding and
analysis of customer behavior, choices, and preferences. The integration of real-time data with
customer information and managing the demand and inventories as per the customer requirement
will also be a measure of success. Customer communication and interaction levels will also
determine the organization success. All of these processes will be possible to be managed using
Big Data tools. Big Data analytics along with decision-support systems and automated data
analytics tools will enable these key tasks.
Step 5: The business initiatives of M&S include enhancement in in the percentage of customer
loyalty card, enhanced customer engagement, and promotion of seasonal clothes with discount.
The automated analysis of customer data and preferences will make sure that the initiatives are
practically carried out and achieved.
Step 6: The Big Data tools will be integrated with the existing information sets of M&S to make
sure that the business strategy is achieved.
Alignment of Business Goals and Objectives: BI and Big Data
The primary goals of M&S are to enhance the customer engagement and satisfaction levels along
with the expansion of customer base. The business goals and strategy of the company can be
aligned with Big Data and BI concepts as explained below.
 Online Analytical Processing (OLAP)
There are various data sets that are associated with M&S. It is certain that not all of these
data sets will be valuable or relevant to the organization. The use of OLAP will discard
the data sets not needed and the ones that will be required will be retained. The use of this
technique will ensure that in-depth analysis of the customer data is carried out (Olap,
2016)
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Big Data & Decision-Making: Marks & Spencer
 Data Analytics
The use of Big Data tools will allow the analysis of the customer data and information
collected from the data sources, such as customer purchase patterns, transactional data,
mobile application, social media etc. The patterns and trends involved with the data sets
will be identified and utilized to the fullest (SearchDataManagement, 2016).
 Data Warehousing
M&S makes use of data warehouses that can be classified in two types as logical and
physical data warehouses. The co-relation between the customer demands, purchase
patterns, market demands, and choices will be developed with the application of this
concept (Villanova University, 2016).
 Data Mining
Big Data and Business Intelligence techniques can be utilized to the best of their
capabilities when the two are integrated with each other. The primary goal of BI concepts
as well as Big Data is to manage the information and data sets. Data Mining under BI will
provide M&S with the ability to identify the relationship between customer behavior and
purchase patterns along with the market demands, company sales, etc.
 Real time BI
The real-time information will be required to be synced with the customer data to allow
M&S to achieve it business goals and objectives. The use of real-time BI will allow the
organization to make business decisions as per the market situation and demands. The
inventory management will also be adequately done. The customers may be provided
with the promotional offers and deals as per their purchase patterns to enhance the level
of interaction and engagement.
 Reporting
M&S is currently working in the product categories as stylish clothing, home
improvement products, and quality food. There is a vast supplier and customer network
that is associated with the organization. The use of BI and Big Data in the reporting
activities will ensure that the reporting structure is streamlined.
 Data Sources
M&S has a supplier network of over 3,000 suppliers. There are a total of close to 1,300
stores of the organization globally. As a result, there are abundant sources of the data sets
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Big Data & Decision-Making: Marks & Spencer
that are associated including the social media channels, external, and internal sources.
These data sources will include Customer purchase patterns, transactional data, social
media channels and network, customer and supplier contact details and demographic
information, site search, and data from the mobile application.
Advantages
 The involvement and use of Big Data will make it possible for M&S to carry put
predictive analysis on the data sets. The customer preferences and patterns will be
identified as a result.
 There are abundant sets of data that are involved with the organization. These huge
clusters of data will be managed adequately using Big Data tools and the streamlining of
the data sets will be possible.
 The customers will be provided with the products as per their demands which will
enhance their engagement levels with the organization.
 The handling and management of the supplier information will also become easier with
the use of Big Data which will lead to the improvement of the supplier relations (Ap-
institute, 2016).
 The irrelevant data sets will be discarded which will lead to better organization of the
storage space.
There are various other advantages that the use of Big Data will offer to the organization.
 Cost Savings
Big Data tools can be customized according to the requirements of the business
organization. There are several Big Data tools that are available in the market and the one
that is currently being used in M&S is Cloudera platform. The platform has been
designed as per Apache Hadoop architecture and it can be easily scaled up or down as per
the business requirements. The data sets and their requirement in the organization will not
remain the same all throughout. It is a dynamic process in which the data needs may
fluctuate. The use of these tools will allow easier management of the data sets, easier
maintenance, and implementation which will bring down the overall costs.
 Competitive Advantage
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Big Data & Decision-Making: Marks & Spencer
M&S is a market giant in the field of clothing and retail. There are several other
organizations that are working in this area and there are also new entities entering the
market. As a result, the level of competition in the industry is huge. It is required that the
organization offers the customers with good quality product along with streamlined
services so that the competitive advantage is gained. The use of Big Data tools will
ensure that the products are released as per the customer requirements and expectations
which will enhance the customer engagement levels.
 New Business Opportunities
The use of Big Data analytics may provide M&S with the opportunity to explore new
business areas in order to expand the customer base. The revenues and profits of the
organization will also improve as an outcome.
Technology Stack
Cloudera Platform & Hadoop Ecosystem
The Big Data tool that is currently being used in the organization is Cloudera platform that has
been designed as per the Apache Hadoop Ecosystem.
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Big Data & Decision-Making: Marks & Spencer
Hadoop Ecosystem
The Hadoop Ecosystem has been developed using JAVA as the programming language as all the
codes and algorithms are developed using this language. The use of this language was done as it
is object-oriented in nature and allowed the tool to have the properties as inter-operability,
platform independence, robustness, and ease of maintenance. The data sets and their requirement
in the organization will not remain the same all throughout. It is a dynamic process in which the
data needs may fluctuate. The use of these tools will allow easier management of the data sets,
easier maintenance, and implementation which will bring down the overall costs (ITProPortal,
2013). Hadoop Distributed File System (HDFS) is the file system that is involved in the tool and
is placed at the bottom of the architecture. The Hadoop architecture is used to store the data sets
and is also involved in the data backup processes. The recovery of the data sets can be done
through Hyper-scale storage architecture (Computerweekly, 2016).
M&S Technology Stack
The technology stack of M&S is shown in the image below.
M&S technology Stack
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Big Data & Decision-Making: Marks & Spencer
The technology stack of the organization comprises of the data sources at the bottom. There are
abundant sources of the data sets that are associated including the social media channels,
external, and internal sources. These data sources will include Customer purchase patterns,
transactional data, social media channels and network, customer and supplier contact details and
demographic information, site search, and data from the mobile application. Hadoop and data
warehouses are present at the top of the data sources. M&S makes use of data warehouses that
can be classified in two types as logical and physical data warehouses. The co-relation between
the customer demands, purchase patterns, market demands, and choices will be developed with
the application of this concept. There are a wide range of databases that the organization makes
use of. These include SQL databases and MySQL database along with a range of NoSQL
databases as well. NoSQL databases that are being used include MongoDB, CouchDB, etc.
NoSQL refers to No-Structured Query Language. These databases do not include SQL in its
architecture and are usually placed on the cloud. As a result, they offer enhanced mobility and
flexibility to the organizations in which these are implemented. These come with enhanced
performance as well (Pentaho, 2016). Documentation and customization of the UI are the other
advantages that are offered with the use of NoSQL databases (Goes, 2016).
Data Analytics along with MDM: Support to DS and BI
Master Data Management (MDM) is the concept that plays a significant role in the case of M&S
data management and organization. It is being used with the decision support systems, Big Data
tools, and BI concepts for data storage, data handling, and management. There are two forms of
MDM that are involved and are used in M&S.
 Operational: There is a lot of transactional data that is involved with the company. The
transactional data needs to be consistent and it is also essential that the integrity of the
data sets is maintained. The use of operational MDM makes sure that the performance is
maintained and improved at all times.
 Analytical: There are BI concepts as data analysis and OLAP used with the MDM that
make sure that the customer data and information is adequately analyzed at all instances.
The amalgamation of data analysis and MDM allows M&S to achieve the following set of
benefits.
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Big Data & Decision-Making: Marks & Spencer
 The synchronization of the customer data and supplier data becomes easier and
simplified.
 The overall response time and throughput time spent in data gathering and analysis is also
brought down.
 Operational management and consistency is managed and is also improved.
 The overall performance of the operational and transactional activities can be improved
upon (InformationWeek, 2016).
Support & List of NoSQL Databases for M&S
NoSQL databases do not include SQL in its architecture and are usually placed on the cloud. As
a result, they offer enhanced mobility and flexibility to the organizations in which these are
implemented. These come with enhanced performance as well. Documentation and
customization of the UI are the other advantages that are offered with the use of NoSQL
databases. The NoSQL databases being used in M&S include MongoDB, Cassandra, and
CouchDB. MongoDB is an open-source database that does not have any set-up or
implementation cost associated with it. It is deisgned using agile as the framework and therefore,
it offers enhanced flexibility and scalability to the organization. Cassandra is the NoSQL
database designed by Apache and it is also open-source in nature. CouchDB has a unique
property of enhanced index management.
There are also some other NoSQL databases that M&S can make use of. These include
Elasticsearch as one of the NoSQL database. The database will support the RESTful web
services and will make sure that the implementation of these services is efficiently done.
AmazonSimpleDB is another database that will enhance the quality and performance of data
management. Terrastore and MarkLogicServer are the NoSQL databases that will enhance the
data storage and handling capabilities (Bigdata-madesimple, 2014).
Social Media and it role in Decision Making
Decision making processes and activities will benefit a lot with the adequate use of social media
in M&S. One of the prime data sources for M&S is the social media channels and networks.
There are millions of customers that are connected with the organization through its social media
presence. The suppliers, customers, and competitors are connected with the organization on the
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