SWOT Analysis of Business Data and Analytics in Independent Grocers of Australia (IGA)

This paper conducts a SWOT analysis on the use of business data and analytics in Independent Grocers of Australia (IGA) in Brisbane to provide better ways for the utilization of business data and analysis in the firm.

Introduction
It is with no doubt that the supermarket business realm has evolved over time to become more
competitive and diverse therefore necessitating different approaches for businesses to be
sustainable (Ahmadi, Dileepan and Wheatley, 2016). Moreover, the tremendous development in
the fields of big data, data analysis and analytics have posed much benefits besides having its
downside. The aim of this paper is to the use of business data and level of analytics, conduct a
SWOT (Strength, Opportunity, Weakness, and Threats) analysis on business data and level of
analytics as adopted by Independent Grocers of Australia (IGA) in Brisbane so that to provide
better ways for the utilization of business data and analysis in the firm.
Big data and data analysis
Business problem and the role of big data
One of the main challenges that Independent Grocers of Australia (IGA) have faced is the issue
of increased competition which subsequently threatens to dwindle the market share held by the
firm. In the recent past, the firm has adopted aggressive price promotions which has ideally
defended the firm’s sales/share. In 2017, the firm adopted Big data as a means with which to
derive vital information when making business decisions (Industry Insider,2018).
Big Data
In the data world, business data has over time become synonymous with big data which is a large
or complex set of datasets (Bowen, 2019). In the Australian supermarket and groceries business
context, there are 2 types of business data which are mostly utilized i.e. scan data as well as
panel data. Scan data or EPOS is the data that is gathered in-store when items are sold or

‘scanned’ at the counter. Such data offers a huge deal of numeric data including units sold, price
of the product sold, time of day that the product is sold etcetera.
After collection of the scan data, the business firm further collects panel data whose aim is to add
substantial depth to the scan data as the consumers join the panel and take their shopping to their
homes and scan the purchases. Therefore, the panel data consists of other consumer data
including consumer’s age, number of persons in household, income levels etcetera. Main
Providers of panel data in Australia are IRI and Nielsen from where the IGA obtain panel data
too.
Level of analytics
In 2013, IGA firm adopted the services of Quantium, a data analytics company based in Sydney
Australia. So according to the CEO Metcash Jeff Adams, “…we can better understand the needs
of our customers and deliver a better shopping experience.” (Bowen, 2019).
Role of Quantium
Quantium mainly specializes in:
i. Data cleansing and curation
ii. Data ecosystem
iii. Data monetization
iv. Applied analytics
All of the activities of Quantium are powered by Q, which is “…a cloud based data science and
artificial intelligence platform, integrating 16 years of Quantium’s IP into one powerful
platform” (Quantium,2019). The firm collects, analyzes, monetizes datasets, generates insights
as well as creates decision support tools for the IGA’s firm. Further, the firm delivers actionable

commercial solutions to enable reshaping of the business and adopt to the market, to the
groceries categories and even the society at large
SWOT analysis
Given below are the Strengths, Weaknesses, Opportunities, and Threats for the use of business
data and data analysis by Independent Grocers of Australia (IGA).
Strengths
1. After up to 6 years of incorporation of Big Data into the business processes of IGA, the
enterprise has begun to realize benefits. In reference, authors of the report “Big data,
analytics and the path from insights to value” note that the use of Big Data and analytics
increases the chances of the business to be a top performer in their market up to two
times (LaValle, Lesser, Shockley, Hopkins & Kruschwitz, 2011).
2. Adoption of big data collected through scan and panel methods has provided means with
which to obtain information on the trends on shopping by the consumers, their
preferences, what time they shop, the shoppers’ age, etcetera
3. Quantium being one of the biggest players in the data analytics industry provides a
reliable source of data analytics to the Independent Grocers of Australia (IGA)
management thereby facilitating the process of decision making which to the largest
extent determines the direction of business operations hence the success and
sustainability of the business.
Weaknesses
1. One major weakness that is prone to arise from adoption of big data and analytics is
probability of drawing poor quality conclusions and insights gathered from the data.

Given the amount of collected data, it requires sophisticated technology and well trained
specialists to handle such kind of data spanning up to petabytes. According to Shaw
(2014), “understanding the data that you are looking at and the quality of the data that
you are analyzing could be a major weakness.”
Opportunities
Herein in big data and analytics, lies vast opportunities likely to benefit both the firm and the
consumers of Independent Grocers of Australia (IGA). Such opportunities include:
1. Collection of big data upon which analysis is conducted so as to obtain insights, will
enable determination of consumer preferences on various items given different times and
hence enable customization of both services to such consumers. Therefore, business data
and analysis will enable the firm to be able to improve customer services hence promote
loyalty.
2. In addition, big data enables analysis of market hence giving the firm an edge on how to
compete favorably in the supermarket and grocery market.
Threats
The major threat to business data and analytics in IGA is the integrity of data which might be
compromised given the growing cases of cyber-attacks. Moreover, reliance on a third party to
deliver analysis and data collection services might slow down the decision-making process.
Recommendations
Given the above SWOT analysis, the following recommendations are made:

i. The firm should incorporate more data collection techniques so as to ensure all aspects of
consumer activities conducted in the supermarket are collected which might so as to
further provide better services and help determine factors that influence decisions made
while purchasing products
ii. Further, the firm should adopt internal data analysis mechanisms to act as a validation
tool to the insights made by Quantium data analytics company. This will improve ensure
the integrity of the decisions made by the management.

References
Ahmadi, M., Dileepan, P., & Wheatley, K. (2016) A SWOT analysis of big data. Education
for Business, 91(5), pp. 1-6. DOI: 10.1080/08832323.2016.1181045
Bowen, T. How Supermarkets Are Using Big Data & Predictive Analytics to Win (+
Infographic). Retrieved from:
https://expert360.com/resources/articles/supermarketretail-big -data
Industry Insider. (2018). IBISWorld reveals state of the supermarkets and grocery industry.
Retrieved from: https://www.ibisworld.com/industry-insider/press-releases/checkout-
update-q1-2018-ibisworld-reveals-the-state-of-play-in-the-supermarkets-and-grocery-
stores-industry/
LaValle, S., Lesser, E., Shockley, R., Hopkins, M., & Kruschwitz, N. (2011). Big
data, analytics and the path from insights to value. Retrieved from:
http://www.analytics-magazine.org/special-reports/260-big-data-analytics-and-the-path-
from-insights-to-value.pdf
Shaw, J. (2014). Why “big data” is a big deal. Harvard Magazine. Retrieved from:
http://harvardmagazine.com/2014/03/why-big-data-is-a-big-deal