How Supply Chain Data Mining Drives Company Growth

Companies looking to improve their bottom lines are turning to data mining and analysis in order to maximize efficiency of stocking practices and thus positively impact profits in the long run. Data mining involves taking a look at the big data collected by a company and pinpointing how the business could do better in terms of where and when spikes in demand occur, among other considerations. According to Shelly Palmer, a business advisor writing for The Huffington Post, a useful data mining algorithm could offer the vital push for companies to achieve and maintain momentum in their growth.

Food retailer Unified Grocers is one company using data mining in order to help maximize profits. According to Supermarket News, the company is using data collection methods to gather information from 800 of its member stores and tracking demand.

“We’ll use that information to help members drive top-line sales and also use the data internally to help make better decisions based on consumer demand rather than just warehouse movement,” Sue Klug, executive vice president and chief marketing officer, said at the annual convention of the Western Association of Food Chains in Palm Desert, California, according to Supermarket News.

Effective management of data can lead to increased profits, and Unified Grocers is only one company using data mining methods to drive a higher bottom line. For example, in 2004, Linda M. Dillman, Wal-Mart’s chief information officer, told her staff to analyze sales data before Hurricane Frances hit the U.S., according to The New York Times. This data was collected from checkouts across the nation and then analyzed according to regional demand for certain things. Data analysts found that, of all things, strawberry Pop-Tarts were among the food items most purchased before a tropical storm. As a result, the company pushed more of that particular product to its coastal stores and ended up selling most of it.

Incorporating the Results into Your Warehouse

The act of data mining is only one step in the journey to higher profits. An effective warehouse management system is also essential for companies to keep track of demand and know when, where and what to send to stores. Implementing automated data collection can help suppliers remain more aware of their inventories because by using accurate reporting methods, the chance of mistakes occurring decreases.

According to RFgen consultants, when businesses experience the kind of growth that data mining can provide, it’s an opportune time to rethink how their warehouses and retailers work. Companies can redesign workflows and invest in technology and infrastructure. An example of this kind of reevaluation would be to incorporate automated data collection into business processes – after all if a company is using big data analysis to increase profits, its warehouses are going to need to accommodate that growth. Streamlined data collection processes are one part of that big picture.