Harnessing Big Data to Predict Demand Across the Supply Chain, from Auto Service World.
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.