Introduction
Technology has revolutionized the face of several businesses across the world. It has transformed the way the selling of products and services was done, or how clients were targeted. Technology is dynamic and so it keeps changing with time. Each and every passing day comes with new ways of doing things. Among the types of technologies that have gained immense popularity in the recent past include such technologies as big data analytics, artificial intelligence as well as machine learning. These inventions in the area of technology come along with many benefits not only on the side of businesses but also on the part of customers. Walmart, for instance, is an example of the Fortune 1000 Company that has benefited immensely from integrating big data analytics and business intelligence.
Company Discussion
Walmart Inc. is a U.S. multinational corporation that runs a collection of supercentres, grocery stores as well as discount department stores (walmart.com, 2022). Walmart has its headquarters in Bentonville, Arkansas. The retail corporation was founded in the year 1962 by Sam Walton. Walmart had close to 10,566 stores as well as clubs operating in 24 nations under diverse names by October 31 of 2021. Walmart Inc. is the biggest corporation on the globe by revenue, with a revenue base of $743 billion (fortune.com, 2021). The multinational corporation is equally the world’s biggest private employer with more than 2.2 million workers. The company was ranked the largest retailer of groceries in the United States in the year 2019. A whopping 65percent (%) of the company’s $10.329 billion worth of sales came from the company’s operations in the United States of America (Sharma, 2011). This paper will thus make a deep dive on Walmart and its use of technology to simplify operations and drive sales. It will majorly look at the company’s efforts to integrate big data analytics and business intelligence and the success stories of that endeavour.
Walmart’s Approach to Big Data Analytics and Business Intelligence
Walmart is with no doubt a giant in the retail sector. The statistics speak for themselves. The company has over 245 million clients making their way to more than 10,000 Walmart stores and websites all over the world. The multinational corporation gathers close to 2.5 petabytes every hour of unstructured data coming from a million clients. This particular data is later generated by the company every hour and equals to 167 times the American Library of Congress’ books.
The company has all along been undertaking big data analysis in an attempt to offer the best e-commerce technologies in order to subsequently deliver a better customer experience (Weerakkody, 2017). The chief objective of leveraging big data at the company is to ensure the optimization of the client’s shopping experience when in the company’s stores, or even in their websites browsing through. The big data solutions at the world’s biggest retail corporation are created with the sole intention of redesigning the world websites as well as developing more innovative apps that are responsible for customizing the shopping experience of clients when in their various stores. For example, the NOSQL and Hadoop technologies are employed to offer the internal customers with a secure breakthrough to the real-time data gathered from diverse sources and effectively centralised for use.
What the Company is doing Right
Big data analytics with business intelligence enable an organization to organize their data so that it can easily be retrieved and analyzed when need arises. This data can be used by decision makers to make rational decisions regarding performance as well as future projections of a company (Wei-Chih Yeh, 2017). As for Walmart, they do not use business intelligence processes just like normal software but as a holistic approach in the day –to-day running of their operations.
Walmart Inc. depends on big data and business intelligence to obtain the real-time information on workflow in their pharmacies, throughout their e-commerce centers and stores, and distribution centers. Therefore, the company has been able to rightly use the technology to ensure the pharmacies are working efficiently. They are employing the use of simulations in the pharmacies to be able to find out the total number of prescriptions that are filled in a single day. This further enables them to know the busiest times of the day, week, month, and year respectively. This data is helpful to the staff as well as the pharmacies themselves in scheduling and to lower the amount of time a prescription takes to be filled.
The company has been able to use the technology to enhance store checkout. By using predictive analytics, the various company stores can expect demand at some specific hours to and determine the number of associates that are required at the counters and centers. By undertaking data analysis, Walmart can be able to determine the proper forms of check out for each and every store.
What the company is doing wrong
The company has depended on the correlation generated by big data analytics, and as a result a very vital brick is missing; the causation. The best way of locating the reasons behind the behavioral patterns is to go ahead and counterbalance big data with what can be called small data. The small data does not grow in warehouses but it can be picked meticulously from the interaction with customers in their respective homes. This could, further be a way bringing empowerment to retailers to be more competitive. I think it can be very interesting to datafy consumer behaviour and have it turned into small sets of data as a causative technique.
What Walmart can do to Improve?
I support Walmart’s approach to big data analytics with business intelligence and the role they have played towards the company’s success. However, I think finding the right balance between correlation and causation can be the way to go for Walmart. If the company needs glean proper insights, they should construct a partnership between big data and small data. For Walmart, the results of such lack of balance might be the reason for the corporation’s problems, some of which are the low customer turnouts these days.
Conclusion
Technology has opened new paths for e-commerce and compelled all the retailers across the world to offer better satisfaction as well as quality services for their clients. Among the types of technologies that have gained immense popularity in the recent past include such technologies as big data analytics, artificial intelligence as well as machine learning. These inventions in the field of technology come along with many benefits not only on the side of businesses but also on the part of customers. Walmart Inc. is one company that has a robust approach to big data analytics together with business intelligence. This technology has enabled the multinational corporations achieve a great deal of benefits. For instance, the company depends on big data analytics to obtain the real-time and concise information on workflow in their pharmacies, throughout their e-commerce centers and stores, and distribution centers. Therefore, the company has been able to rightly use the technology to ensure the pharmacies are working efficiently.
To further ensure proper operations and robust service delivery to their customers, Walmart Inc. should ensure the use of small as well as big data. Striking that right balance will ensure that the company has the right data in its disposal to undertake all their all their operations efficiently and effectively.
References
fortune.com. (2021, October 31). Fortune 500: Walmart Ranked 1. Retrieved from www.fortune.com: https://fortune.com/company/walmartfortune500/
Sharma, R. S. (2011). Everyday Low Price -A Blessing in Disguise for Walmart During Recession. International Journal of Business and Globalization, 7(4), 409-433. doi:10.1504/IJBG.2011.042749
walmart.com. (2022, February 01). Walmart International Corporation. Retrieved from www.walmart.com: https://www.walmart.com
Weerakkody, U. S. (2017). Critical Analysis of Big Data Challenges and Analytical Methods. Journal of Business Research, 70(2017), 263-286. Retrieved from https://doi.org/10.1016/j.jbusres.2016.08.001
Wei-Chih Yeh, S. M. (2017). Big Data Analytics and Business Intelligence in Industry. Information Systems Frontiers, 19(1), 1229-1232. Retrieved from https://doi.org/10.1007/s10796-017-9804-9
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