The automotive aftermarket is spending a lot of money to deliver on its “the right part, the right place, the right time” promise. Progress has been made, but significant opportunity remains for cost savings and margin gain.
The Automotive Aftermarket Suppliers Association (AASA) Technology Council (ATC) introduced a new “Special Report” at its Spring Meeting on March 18, “Harnessing Big Data to Predict Demand Across the Supply Chain,” [http://www.aftermarketsuppliers.org/Doc-Vault/ATC/Harnessing-Big-Data.pdf] focused on harnessing “Big Data” to forecast demand across the entire supply chain. AASA is the light vehicle aftermarket division of the Motor & Equipment Manufacturers Association (MEMA).
Developed with Epicor Software Corporation, “Harnessing Big Data to Predict Demand Across the Supply Chain,” examines the industry’s capability of forecasting demand at the store level. The report finds that next big step for the aftermarket is forecasting demand for the entire supply chain, which will help suppliers employ stock balancing on a macro level. It will help suppliers pull slow-moving or inactive parts and place their products on shelves where they’re most needed, employing stock balancing on a macro level.
“Forecasted demand using ‘Big Data’ will lead to leaner practices for the supply chain, such as manufacturers producing a more accurate volume of parts, and distributors and suppliers stocking the right amounts,” said Chris Gardner, AASA vice president and executive director of the ATC. “With collaboration throughout the industry, the ability to predict future demand throughout the product life cycle will be a game changer.”
The industry is well positioned to take that next step, according to Scott Thompson, vice president, automotive, retail and distribution solutions for Epicor Software Corporation. “There is now a broad-based understanding of the value of Big Data among leading suppliers and distribution organizations,” he said. “It’s our goal at Epicor to help the industry to move beyond simple analytics to predictive analytics – from the micro view to the macro view.”
“Harnessing Big Data to Predict Demand Across the Supply Chain” is available at the ATC website:www.aasatechnology.org.