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Walmart’s Operations Management

Walmart has been identified as the world’s largest retailer company with 20,000 stores in 28 countries and over two million employees. With its significant operations, it has eventually seen value in data analytics. Walmart has dramatically grown its big data and analytics department. Walmart’s management used big data to understand the customer’s needs and provide them with what they wanted to buy; hence it drives the business performance. This paper aims to review and understand the operations of the business.

First, we will review the significant data business drivers for Walmart (Marr et al..,23). The first data is unstructured. This is information that isn’t stored in a structured database format. It analyzes service center comments to identify customer service training opportunities. It also integrates social media, online reviews, and voice data from the system for improving product and service quality. The second business driver is structured data. This is when information is standardized and can be easily accessed by humans and programs. It strengthens customer service data to improve the customer service experience and boosts customer account history and credit card usage to determine customer value. It also supports store-level data to analyze the seasonality of data, and data is also maintained to determine which product to stock and what to discontinue.

The third business driver is data velocity. It strengthens weather and local event data for inventory management, social media data for sentiment analysis, and public employee reviews to improve employment practices. The last business driver is predictive analytics. It uses a store credit card, economic data, and social media to forecast demand and analyze market data, customer data, and shopping patterns to recommend products and determine preferences.

Big data applications support porter’s five forces analysis (Burbach et al..,83). The first porter force analysis is a moderate force for new market entrants. Small firms offer low-cost substitutes to enter the market, and through their operations, they remain profitable. The extensive data application supporting this analysis enhances the online Walmart marketplace to grow small-scale suppliers to sell directly on their online platform. The second analysis is buying power which is a weak force. Buyers who make small purchases cannot pressure retail firms on prices hence the application being customer satisfaction optimization.

The third force is product/technology, which is a weak force. The marketplace has few or no available substitutes. The ones available are not at the low, competitive cost that Walmart offers, and its application is an innovation by customer needs. The other force is supplier power which is a weak force. Suppliers face competition between themselves since they do not have any bargaining power. Its application is to optimize supply chain coordination to minimize storage. The last power is a competitive rivalry which is a strong force. Walmart gets its competition from companies like Amazon. Its application scans competing prices to ensure that costs are consistently low.

Walmart has a value chain analysis that includes primary and secondary activities (Fernandez et al..,76). The first primary activity is inbound logistics. It uses data to optimize supply chain logistics, while the second primary activity is outbound logistics which uses data to optimize distribution for warehouses to support deliveries. The other activity is operations that use data for customer spending history. In contrast, the other activity is sales and marketing, which uses social media data for advertising across channels and launching campaigns. The last activity is service which returns data to optimize returns operations. The first support activity is the infrastructure which analyzes traffic data in major cities to determine building needs. At the same time, the other is human resources which uses return data to identify training opportunities for staff with scanning errors. The third activity is technology which uses actual-time weather to alert suppliers of shortages. In contrast, the last activity is procurement which uses product sales data to manage relationships with suppliers.

Works Cited

Marr, Bernard. Artificial intelligence in practice: how 50 successful companies used AI and machine learning to solve problems. John Wiley & Sons, 2019.

Fernandez-Stark, Karina, and Gary Gereffi. “Global value chain analysis: A primer.” Handbook on global value chains. Edward Elgar Publishing, 2019.

Burbach, Christian. “Walmart Strategic Analysis.” (2021).


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