The Future Technology for Kmart New Zealand: Big Data Analytics and Cloud Computing

This essay discusses the potential of big data analytics and cloud computing for Kmart New Zealand to improve customer experience, inventory management, and supply chain visibility. The use of big data analytics can help in improving the shopping experience, gaining visibility into promotional performance, and personalizing campaigns. Cloud computing can aid in supply chain processes, inventory management, and communication between departments. The essay also highlights the importance of enterprise-wide supply chain visibility and real-time status information.

Title: The Future Technology for Kmart New Zealand
Essay

Contents
Introduction......................................................................................................................................1
Discussion........................................................................................................................................1
Conclusion.......................................................................................................................................3
Bibliography....................................................................................................................................4

Introduction
With the growth of the big data, the study is about how the data processing application software
are adequately able to handle the sharing, and the transfer of data sources. They are conducted
through the concepts of volume, variety and the velocity. The big data is about using the
predictive analytics with user behavior that will help in extracting the value from data and
particular size of the data set (Yang, Huang, Li, Liu, & Hu, 2017). The use of cloud computing is
effective for configuration of the different system resources that helps in the minimal effort for
the management over the internet. The cloud computing generally relies on achieving the
coherence with the economies of scale that are found to be similar to the public utility. The aim
of the research is to work on the big data analytics which will be effective for Kmart New
Zealand. Kmart is the company which has been working on providing the customers with lower
prices through more than 200 stores in and around Australia and New Zealand (Fernández et al.,
2014) . The company needs to ensure about getting the lowest prices which are for the items that
are needed by the families every day.
Discussion
The Kmart can accept the big data analytics which will help in improving the customer
experience decisions with retailer and brands making use of retail analytics to anticipate about
the needs of the shopper. The company can help in improving the shopping experience with
improving the satisfaction of customer and repeated purchases, and customer referrals as well.
The retail companies can use the data insights which are for capturing in pockets and gaining a
view of business results. It includes the consumer trends and growth strategies that will require to
unify and integrate the data. The gaining visibility into the promotional performance can help in
adopting the marketing and forecasting tactics for identifying the seasonal trends with items and
opportunities to sell the revenue (Inukollu, Arsi, Ravuri, 2014). The transactional data is from the
off-counter purchases with loyalty programs and the in-store queries which have been for the
retailers. The multiple channels could approach the retailer to add an advantage with efficiency
systems for collating, storing and comprehending the data sets.
The balanced decisions need to be made for the consumer behavior analytics which is for
the retail and how the critical tackling of the challenges like the improvement in the conversion
rates are there (Jin, Wah, Chang, & Wang, 2015). The personalization of the campaigns and then

handling lowering customer acquisition cost is an effective method. The personalization of the
in-store experience with big data includes how the online sales tend to grow with the new trends
that have been emerging where the shoppers tend to perform for the physical research based on
the products in-store and online. Kmart NZ could include the increased sales through the
different channels where the data engineering could turn the data resources into major
competitive advantage. The use of the websites point of sale system, mobile apps and the supply
chain systems are helpful for improving the different marketing and the merchandising tactics on
the consumer behavior (Bahrami & Singhal, 2015).
The increased rates of conversion through the predictive analytics and the targeted
promotions leads to lowering the costs and the retail companies also tend to target customer
promotions. It requires 360-degree view of customers and the customer information is also
limited to the demographic data that is collected at the time of sales transactions. The big data
analytics is for the quantification of different promotional tactics with using a consumer purchase
and browsing history to properly identify the needs for the customers. There is a need of
customer purchasing behavior and social media activity for driving timely offers to incent the
online purchases (Chen & Zheng, 2014). The customer journey analytics is determined with
empowerment and connections. The channels like the mobile and the social media could access
the different kinds of information where the customers expect more that helps in reflecting the
preferences, history and interest. The marketers also need to adapt on understanding and
connecting with the customers (Riggins & Wamba, 2015). This requires a proper insight related
to data driven standards that can easily help in understanding the customer journey in and across
the different channels. The operational analytics and the supply chain analytics is for the faster
product life cycles and the operations that cause the retailers to make use of the big data analytics
and reducing the costs as well. The retailers are working with intense pressure to optimize the
asset utilization and the service quality. The key is to perform the data engineering platforms for
increased efficiency and unlocking the insights for different trends, patterns and the outliers.
With this, the cloud computing has been effectively able to help in improving the
interaction with the customers that will be a boon for Kmart NZ. The people will be able to shop
and get their billing done very quickly that can lead to satisfying the customers and improving
the process of business as well (Sookhak, Gani, Khan & Buyya, 2017). The cloud aids the supply

chain process where the improvement of technology services are important with investment in
cloud collaboration platform. The example is how Cloud Collaborate could be used for the real
time status information with streamlined inventories and tracking the deliverables as well. The
development of the products in the cloud is also effective of costs with reduced spending. The
cloud technology allows the retailers for saving the money for Kmart NZ and then help in
improving the day-to-day operations as well. The communication is between the departments
which becomes easy and the success goals are in retail which becomes less complicated and
achievable with help of cloud-based technology. The technology helps in allowing the people to
make decisions and empowered the staff which makes their life easy. The cloud technology has
been important for the company as it will be helpful in the growth from integrating and
switching. The retail industry is adapting the cloud computing as it helps in bringing a revolution
to the core business strategies. The retailers are able to find themselves competing in the
marketplace which is mainly dominated by the use of mobile devices. There are 80% of the
people and customers who will make use of the mobile device for informing their purchase
decisions. The mobile first mindset has compelled the retailers to focus on seamless mobile
experience for the customers. The savvy retailers have been able to focus on the mobile friendly
options and better sales offers. Kmart NZ has been putting in efforts to use data analytics for
making number-based decisions about what to produce and sell (Gai, Qiu, Zhao & Xiong, 2016).
The management of inventory can also help the retailers to work with overlooked recovery of
data disaster where cloud computing enables to continue for better business operations as the
data and apps are stored in the cloud. The cloud computing can help in improving the different
operations of channel where the retailers can work on simplifying the systems and then deliver a
more personalized customer experience. The Retail as a Service (RaaS) is about integration of
different verticals like the inventory and order processing through improvement in the re-
stocking capability. The higher supply chain visibility is to make use of enterprise wide supply
chain visibility where the retailers are capable of handling business without any sort of stock-
outs and expedited deliveries. The cloud helps in the campaign of the real time status of the
documents from the suppliers, logistics providers and the carriers.
Conclusion
The use of big data analytics has been for the remote servers which are hosted on the internet for
managing, storing and then processing the data (Cui, Yu & Yan, 2016). The cloud computing

helps in improving the world’s economy with huge potential that is about handling the reduced
IT costs and simplifying the systems and competition leveraging that tends to be increasing. The
personalized customer service can help in improving the customer success management. The big
data can also be able to provide Kmart NZ with personalized offerings and better customer
service. The cloud services can lead to merging in-store data with digital data for offering best
solutions to the customers. There are insights that help in determining the enterprise wide supply
chain visibility. The retailers are also capable of handling the business without any stock-outs, or
higher inventories. The cloud helps in capturing real tie status of consignments with digitized
documents from suppliers, carriers and the logistics providers.
Bibliography
Bahrami, M., & Singhal, M. (2015). The role of cloud computing architecture in big data.
In Information granularity, big data, and computational intelligence (pp. 275-295).
Springer, Cham.
Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and
technologies: A survey on Big Data. Information Sciences, 275, 314-347.
Cui, L., Yu, F. R., & Yan, Q. (2016). When big data meets software-defined networking: SDN for big
data and big data for SDN. IEEE network, 30(1), 58-65.
Fernández, A., del Río, S., López, V., Bawakid, A., del Jesus, M. J., Benítez, J. M., & Herrera, F.
(2014). Big Data with Cloud Computing: an insight on the computing environment,
MapReduce, and programming frameworks. Wiley Interdisciplinary Reviews: Data
Mining and Knowledge Discovery, 4(5), 380-409.
Gai, K., Qiu, M., Zhao, H., & Xiong, J. (2016, June). Privacy-Aware Adaptive Data Encryption
Strategy of Big Data in Cloud Computing. In CSCloud (pp. 273-278).
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The
rise of “big data” on cloud computing: Review and open research issues. Information
Systems, 47, 98-115.
Inukollu, V. N., Arsi, S., & Ravuri, S. R. (2014). Security issues associated with big data in
cloud computing. International Journal of Network Security & Its Applications, 6(3), 45.

Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and challenges of big data
research. Big Data Research, 2(2), 59-64.
Riggins, F. J., & Wamba, S. F. (2015, January). Research directions on the adoption, usage, and
impact of the internet of things through the use of big data analytics. In System Sciences
(HICSS), 2015 48th Hawaii International Conference on (pp. 1531-1540). IEEE.
Sookhak, M., Gani, A., Khan, M. K., & Buyya, R. (2017). Dynamic remote data auditing for
securing big data storage in cloud computing. Information Sciences, 380, 101-116.
Yang, C., Huang, Q., Li, Z., Liu, K., & Hu, F. (2017). Big Data and cloud computing: innovation
opportunities and challenges. International Journal of Digital Earth, 10(1), 13-53.