Analysis impacts staffing, merchandising decisions
“Big data is an essential part of the strategy of many companies, and Walmart is analyzing data in distinct ways,” the post notes, going on to detail five areas where Walmart is using “big data to enhance, customize and optimize the shopping experience.” They are:
- Making pharmacies more efficient. Walmart uses an analysis of simulations in its pharmacies to find out how many prescriptions are filled in a day, and determine which times of the day or a month are busiest. That information is then used to help the pharmacy with staff scheduling, so that it can fill prescriptions faster and at a lower cost.
- Improving store checkout. Walmart is also testing ways to use big data to improve the store checkout experience. As with the pharmacy, that involves using predictive analysis to determine how many cashiers are need at particular times of the day. But Walmart is also using data to decide what kinds of checkout lanes, including self-checkout and facilitated checkout, are appropriate for each store.
- Managing the efficiency of supply chains. Walmart is also using simulations to track the number of steps needed to move products from the shipping dock to the store. The retailer can then find ways to optimize the route and reduce the number of times the products need to be handled along the way. Walmart is also using data to make its own trucking fleet more efficient, including scheduling driver times and keep costs down.
- Optimizing product assortment. Walmart says it can analyze customer preferences and shopping patterns to speed decisions on how store shelves should be stocked and merchandise displayed. Big data also provides insights on new items, discontinued products and which private brands should be carried, the company says.
- Personalizing the shopping experience. The retailer notes that it can use data analysis to offer personalized rollback deals to shoppers.