MG413: Data Insights for Business Decisions - Sainsbury's Case Study

This report provides an in-depth analysis of data insights for business decisions, focusing on Sainsbury's supermarket chain. It evaluates the types of data used and collected by the company, differentiating between orthodox market research and big data. The report explains data storage methods, assesses the impact of technological developments on decision-making, and analyzes the strategic importance of data in daily operations. Furthermore, it provides recommendations for improving data capture and usage within the firm, concluding that big data technology is essential for gaining deeper insights into market trends and customer preferences, ultimately leading to more informed and effective business strategies.

MG413
Data insights For Business
Decisions

Table of Contents
Introduction:.....................................................................................................................................3
MAIN BODY...................................................................................................................................3
Evaluation of type of data used and collected by the company:.................................................3
Description of difference between market orthodox and big data:.............................................4
Explaining about the ways in which the information is stored:..................................................5
Description of the impact of technological development on the use of data for decision
making process:...........................................................................................................................6
Analysing about the strategic importance of data in day to day operations of organisation:.....6
Evaluation of ways to improve data capture as well as usage in the firm:.................................7
Conclusion.......................................................................................................................................7
References........................................................................................................................................8

Introduction:
The term big data is termed as large volumes of data that can be in structured as well as
unstructured way. The big data supports the organisation to make facts and evidence based
decision making process. The main purpose of big data is to optimise business process by
gaining an deep insight about the customers of company. For this report Sainsbury's organisation
is taken into consideration. The company is currently the second largest supermarket chain based
in London, UK. The report will cover about the types of data which is used by the company. In
addition to this, the report will highlight orthodox market research and will explain about how
big data is different from this. Moreover, the report will also include about the types of databases
as well as will also cover the impact of technological growth over the decision making process of
firm. Furthermore, the report will also highlight the strategic importance of data for company and
will also present ways for improving data capture.

MAIN BODY
Evaluation of type of data used and collected by the company:
The big data is crucial for the modern companies as it supports the organisation to make
well informed decisions as well as also helps the firm to understand customer wants and desires
in the most effective manner(Singh, 2019). The use of big data assists the firm to analyse
customer trends in the most appropriate manner which directly helps firm to develop and
implement fact based strategies in order to improve its competitive position in market. In context
to Sainsbury's firm, the second largest supermarket chain of UK undertake use of big data tools
which helps the organisation to effectively predict the future demands of the customers. The
collection of data through machine learning supports the company to efficiently know what
products do customers want to buy in future. The Sainsbury's firm exercises use of predictive
analysis that supports the firm to timely detect the trends in grocery market. In addition to this,
the collection of big data also assists the firm to be up to date with the latest market trends going
on in the market. Furthermore, this cloud based analytics tool helps Sainsbury to effectively
change unstructured form of data into classified one which leads to proper usage of information
related to customers or competitors.
Description of difference between market orthodox and big data:
The orthodox market research techniques is considered as the set of traditional techniques
that leads the firm to gather relevant information about the market trends. This old data
collection method is used in order to better understand the customer desires form which the
business can analyse this data with the purpose of designing better products and services. This
market research method undertakes use of surveys, filling questionnaire as well as personal
interviews in order to extract accurate information about current market trends(Upadhyay and
Kumar, 2020).
The difference between market orthodox and big data:
Basis Traditional market research Big data
Definition The orthodox market research
techniques is termed as
method of market research that
supports the firm to collect
The big data is the modern
type of market research
techniques which uses
machine learning as well as AI

necessary information about
customers through practising
traditional way such as doing
surveys etc.
technology while collecting
relevant data about current
market trends.
Time taken The time taken to perform
collection of customer
information is long as well as
tedious(Mishra and et.al.,
2018).
The time taken to collect
customer information through
big data techniques is very less
as compared to traditional
methods of market research.
Tools used The orthodox market research
techniques takes use of
surveys, personal interviews
and many more while
collecting crucial data about
customer wants and desires.
The big data is collected with
the help of modern tools such
as machine learning as well as
Artificial Intelligence.
Explaining about the ways in which the information is stored:
Database: The term database is defined as the structured collection of critical information
or data which is stored in the computer system in electrical format. The following are the three
types of database which will show how data is collected in different ways:
Relational database:
In this type of database, the information is collected and organised in the logically
independent table formats which consists of multiple rows and columns that relate to each other.
This database provides support for the organisation in terms of deleting or updating data
effectively(Giacalone, Cusatelli and Santarcangelo, 2018).
Network database:
In this the data is stored in the form of hierarchical structure. The data in network
database is stored in stored in such a way that ensures all entities are properly structured in
graphical representations.

Hierarchical database:
In this type of database, the information is organised in the tree like shape. This require
the business to access data after passing hierarchical order.
Management information system:
The management information system is defined as software application which helps the
organisation to track and collect crucial information from multiple online systems in order to
make an evidence based decision making after properly analysing the data or reports. The
information is stored in the management information system with the support of doing personal
interviews, practising case studies, through surveys and much more (Al Hadwer, Gillis and
Rezania, 2019).
Description of the impact of technological development on the use of data for decision making
process:
The growth in technology completely altered the way data is collected as well as used in
order to formulate an effective strategies decisions. In context to Sainsbury's company, the
update of traditional market research techniques into machine learning analytical tools supported
the company in the positive manner as the change leads the organisation to make cost effective
as well as more accurate predictions related to current market trends and customer needs and
wants. The innovation of technology gave birth to big data technology that favourably assists the
firm to understand complex grocery trends and also supports the organisation to know timely
about what products are getting famous among their customers. In addition to this, the Big data
technology also helps the company to draw data from multiple online platforms which is kind of
impossible for traditional market research methods. Moreover, the data mining technology has
greatly impacted the usage of data as this technology supports the firm to formulate strategic
plans after analysing the large amount of information in effective manner(Fernando,
Chidambaram and Wahyuni-TD, 2018).
Analysing about the strategic importance of data in day to day operations of organisation:
In context to Sainsbury's organisation, The big data technology supports the firm to make
evidence based decisions by collecting as well as analysing information from different digital
platforms such as social media platforms. The data collected through machine learning and AI
technologies helps the firm to ensure smooth operations of its business activities as well. The Big

data greatly assists the firm to optimise its business performance by gathering accurate market
trends in the most cost effective and timely manner. Moreover, Sainsbury's firm practice the
usage of data drawn from big data technologies towards managing various areas of its business.
The first is that the information collected is used by organisation to grow its better produce. In
relation to this, the firm uses big data information in order to discover better dairy products
through identifying best livestock feeding practices. Furthermore, the big data also supports the
organisation to improvise the process related to how stock is transported to its stores. Along with
this, the firm uses the information in order to track the effectiveness of merchandising displays.
Beside this, the biggest reason for using information by Sainsbury's is to drive the satisfaction
level of customers after assessing properly about their changed preferences and desires.
Evaluation of ways to improve data capture as well as usage in the firm:
The data is most crucial part for the organisation in order to make accurate and data based
decision making for achieving customer satisfaction level. In context to Sainsbury's, the
following effective data capture strategies can support the firm to gather information in the most
efficient manner:
Setting guidelines:
In this strategy, the company can formulate a certain guidelines such as using proper
abbreviations, using capital letters for the top companies with proper spellings. The firm by
setting correct guidelines can prevent duplication of data.
Ensuring compliance and continuity:
The compliance of set guidelines by the staff members of company and continuity can
help the organisation in decreasing the collection of outdated customer information.
Measuring customer transactions:
The firm can enhance the proper capture of data by practising customer reward programs
such as sales coupons or other marketing codes. This strategy can support the organisation in
tracking customers needs and wants in the up to date manner(Rajabion, 2018).
Conclusion
It has been analysed from above report that Big data technology is becoming essential for
the firm in order to gain deeper insights about current market trends as well as customer wants.
The report was able to explain that implementing big data technology in decision making process

support the firm to make timely and accurate decisions. In addition to this, it has been concluded
that big data techniques is better than traditional market research techniques. The report has also
covered about types of databases and management information system. Moreover, it has been
evaluated that technological up-gradation supported the firm to collect data from online
platforms. Furthermore, it has been concluded that collecting data from machine learning and AI
tools helped the firm to improve the efficiency rate of day to day operations.
References
Books and Journal
Al Hadwer, A., Gillis, D. and Rezania, D., 2019, March. Big data analytics for higher education
in the cloud era. In 2019 IEEE 4th international conference on big data analytics
(ICBDA) (pp. 203-207). IEEE.
Fernando, Y., Chidambaram, R.R. and Wahyuni-TD, I.S., 2018. The impact of Big Data
analytics and data security practices on service supply chain
performance. Benchmarking: An International Journal.
Giacalone, M., Cusatelli, C. and Santarcangelo, V., 2018. Big data compliance for innovative
clinical models. Big data research, 12, pp.35-40.
Mishra and et.al., 2018. Organizational capabilities that enable big data and predictive analytics
diffusion and organizational performance: A resource-based perspective. Management
Decision.

Rajabion, L., 2018, December. Application and adoption of big data technologies in SMEs.
In 2018 International Conference on Computational Science and Computational
Intelligence (CSCI) (pp. 1133-1135). IEEE.
Singh, N., 2019. Big data technology: developments in current research and emerging
landscape. Enterprise Information Systems, 13(6), pp.801-831.
Upadhyay, P. and Kumar, A., 2020. The intermediating role of organizational culture and
internal analytical knowledge between the capability of big data analytics and a firm’s
performance. International Journal of Information Management, 52, p.102100.