SAN FRANCISCO, Aug. 10, 2022 /PRNewswire/ — The DecisionNext Price List feature gives users access to all their finished goods pricing and the raw material inputs that drive them.
DecisionNext has announced the release of their Price List module within their commodity analytics software, aimed at connecting the procurement and pricing functions at meat processing organizations.
The Price List module instantly shows expected gross margin for each pricing alternative and empowers users to build a historical log of all pricing details and the risk profiles associated with each price quote.
Michael Farrand, DecisionNext Food & Ag Lead remarked “DecisionNext’s ability to bring proprietary analytics power to the protein industry, across the supply chain from procurement to sales, allows our customers to be on the leading edge of today’s technology. Our new Price List feature is the latest in a growing stable of solutions DecisionNext brings to market which will help set the bar for the next generation of innovative industry leaders to be successful in any market condition.”
Powered by machine learning algorithms, DecisionNext allows market experts to bring together the best of human and machine intelligence to improve market visibility and forecast accuracy through transparent, interactive software. By having the ability to not just forecast markets, but simulate outcomes, decision-makers can more effectively evaluate options in high value, high frequency decisions across sourcing, operations, and sales. Reference customers of DecisionNext include Sysco, Johnsonville, Topco, Teys, and other leading names in the food and agriculture space.
For more information, watch this video.
View original content to download multimedia:https://www.prnewswire.com/news-releases/decisionnext-unveils-new-tool-for-finished-goods-price-forecasting-301603834.html
The content is by PR Newswire. Headlines of Today Media is not responsible for the content provided or any links related to this content. Headlines of Today Media is not responsible for the correctness, topicality or the quality of the content.