Use of Big Data and Predictive Analytics to Achieve a Competitive Advantage

Introduction

Access to valuable market information that shapes the decision-making process and impacts the bottom-line justifies the growing attention in Big Data and Predictive Analytics from businesses. In highly multifaceted sectors, firms maintain a competitive advantage through continuous improvement of activities. The United States (US) grocery industry is a prime example of such an enterprise. Seeing the competitive retail setting, managing a grocery chain can be difficult as there are various products to handle, many of which expire quickly, causing wastage. Grocery retailers enjoy a profit margin of between 1% and 2%; for this reason, they require careful planning and effective publicizing campaigns (Lowery, 2017). Creation of personalized marketing messages, driving in-store sales, and analyzing consumer sentiments are some of the ways through Big Data and Predictive Analytics lets corporations strengthen their activities and remain competitive. Therefore, this research paper will examine how Walmart, Kroger, Safeway, and Costco Wholesale strategically utilize Big Data and Predictive Analytics to augment their competitive advantage.

Industry Overview

Major players in the US grocery sector include Costco, Safeway, Kroger, and Walmart. In 2017, Walmart led the grocery industry possessing over a quarter of the market share. Kroger, the next significant player, controlled more than 10% of the market (Kanakaratne, Bray, & Robson, 2020). Overall by 2020, Kroger and Walmart remained top leaders controlling over 30% of the grocery market, which is line with the figures from 2017. Despite Kroger's and Walmart's substantial lead, according to Lowery (2017), the US grocery industry remains highly disjointed with small chains and independents, including Safeway and Costco occupying the remaining 40%.

The United States grocery industry has changed from a format of pure competitiveness, where small chains and independent grocers sold the same products, each to a constrained end-user base and geographical area. According to Kanakaratne et al. (2020), this phenomenon signifies the original points of the industry’s life cycle. Currently, a small number of big, sophisticated chains serving across states based on oligarchical structure control business operations, presenting the mature stage of its life cycle. The industrial change has created a total revenue of $492 billion, leading to the conclusion that the US grocery market is growing significantly (Yumurtacı Hüseyinoğlu, Kotzab, Köstepen, & Halaszovich, 2020).

Grocers are using Big Data and Predictive Analytics to target potential end-users specifically. According to Yumurtacı Hüseyinoğlu et al. (2020), data utilization has proven to be useful since it is among approaches through which grocers can use collected and analyzed information to enhance their market position. With a 1% average profit margin, grocery store retailers require strategic planning to minimize costs of operations while moving products quickly (Ozgormus & Smith, 2020). Groceries are volume stores; hence, collect a lot of data daily. In the US grocery industry, players use practical data management approaches to analyze and interpret data for future use.

eGrocery represents the future of the US grocery industry since Americans are spending less time shopping. Wood (2013) opined that in a world where people use less and less time shopping, center-store grocery products risk facing the same fate as other good categories before them. Lowery (2017) recognized that they would yield to the changes in the American consumerisms trends. As a consequence, US grocers will reduce the square floorage dedicated to their products, and increase their perimeters to satisfy the ever-changing customer needs. The grocery retailers will adopt new in-store selling tactics for the goods that bridge the gap between physical and digital commerce.

US grocers will develop the industry through collecting and analyzing more data coming as shopping experiences continue to change, and companies implement new technologies. According to Ozgormus and Smith (2020), organizations should have a firm grasp over their data, capitalizing on available technologies to make the most of it. Big Data and Predictive Analytics represent practical solutions (Wood, 2013). They will let corporations make data-driven decisions, concentrate less on the mundane task, or studying multifaceted reports, and focus more on responsibilities that will have a significant industrial impact.

Due to the changing customer expectations, the US grocery industry will no longer operate as it has before, hence players will have to use Big Data and Predictive Analytics to remain competitive. With every single purchase that occurs in-store, retailers collect valuable data regarding an end-user, subsequently using it to enhance customer experience and strengthen their market position (Lowery, 2017). Unlike in the past, currently, in the US grocery industry, companies use data to retain customers and get new businesses since data analytics ensure that they understand their consumer profiles even better. Also, data analytics will let enterprises to gauge the effectiveness of their service delivery, making them more competitive. 

Individual Companies

                    i.            Walmart

In 1962, Sam Walton opened that first Walmart outlet in Rogers, Arkansas. In 1968, the business expanded outside Arkansas, and by the 1980s, it had reached majority of the southern states (Walmart, 2020). By 2020, the company has more than 11,000 stores across 28 countries, making it the largest grocery retailer in the...