Big Data Business Drivers for Walmart

Let’s look at the Big Data Business Drivers for Walmart and data monetization impacts in each of the areas

Porter’s Five Forces Analysis

Big Data applications related to the four drivers that support Walmart for each of the five forces

Buying Power: Weak force. Many buyers who make small purchases can’t pressure retail firms on pricing, overall weak bargaining power.
Big Data Application: Customer satisfaction optimization: Provide personalization, product recommendations.

Product/Technology: Weak force. The marketplace has few or no substitutes. The ones available are not at the competitive low cost that Walmart offers.
Big Data Application: New private label product development: Innovate by understanding customer needs, preferences, and health trends to develop private label brands.

Supplier Power: Weak force. Many individual suppliers face a tough competition between themselves. Suppliers do not have bargaining power. The moderate force exists from a small number of high-end specialty suppliers.
Big Data Application:
Optimize supply chain coordination with the goal of minimizing storage: Determine adjustments to inventory and workflows across stores, distribution centers, pharmacies, and distribution channels.

New Market Entrants: Moderate force Small firms and startups can offer low-cost substitutes and enter the market. Their lean operations keep them profitable.
Big Data Application:
Enhance online/eCommerce Walmart marketplace to grow small and medium scale suppliers selling directly on Walmart eCommerce platform.

Competitive Rivalry: Strong force. Many retail firms and high variety. Highly saturated market with competition from Target, Google, Amazon, Whole Foods, Costco, Home Depot, eBay, and Apple amongst others. Unlike some of its competitors, Walmart has an online as well as brick-and-mortar presence.
Big Data Application:
Scan competition prices and promotional offers to ensure that the pricing offered is always the lowest. Use attribution analysis to optimize marketing spend.

Value Chain Analysis

Primary activities

  • Inbound logistics: Use real-time POS data to optimize supply chain logistics.
  • Outbound logistics: Use real-time POS data to optimize distribution (routing, loading) for warehouses and eCommerce fulfillment centers to support same-day and next-day deliveries.
  • Operations: Use POS data, customer spending history, seasonal sales data to anticipate inventory levels across Sam’s Club, US, and international stores.
  • Sales/Marketing: Use customer spending patterns, social media data, demographics data to advertise across online/offline channels and launch campaigns.
  • Service: Use returns data and customer service transactional data to optimize returns operations, save customer time with returns and enhance customer service.

Support activities

  • Infrastructure: Analyze foot traffic data for stores in major cities to determine building upgrade needs.
  • Human Resources: Use returns data to identify training opportunities for checkout staff with scanning errors. Use sales data to predict seasonal hiring needs.
  • Technology: Use real-time weather, merchandise inventory analysis to alert suppliers of shortages and keep stores stocked.
  • Procurement: Use product sales data, shelf movement to manage strategic relationships with suppliers.




Exec Director StratEx - I bring to the table blend of data science, finance and strategy management skills with 20+ years of experience in insurance & fintech.

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Poonam Rao

Poonam Rao

Exec Director StratEx - I bring to the table blend of data science, finance and strategy management skills with 20+ years of experience in insurance & fintech.

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